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The impact of vehicle traffic volume on pedestrian behavior at unsignalized crosswalks

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
PL
Wpływ natężenia ruchu pojazdów na zachowanie przechodniów na przejściach bez sygnalizacji
Języki publikacji
EN PL
Abstrakty
EN
The research is focused on analyses of vehicle delays caused by pedestrian crosswalks on one-way streets. The study encompassed three particular locations of unsignalized crosswalks: on the street section between intersections, in the zone of intersection impact, and in the zone of intersection itself. The study revealed that the major impact on traffic jams is observed at a distance of 50-100 m from the unsignalized crosswalk. The study analyses pedestrian behavior and waiting time at such crosswalks. It was confirmed that the pedestrians did not immediately use their priority before passing. The paper presents the change in pedestrian waiting time when crossing the roadway depending on traffic flow. Based on that data, a model was prepared and simulations of pedestrian behavior at unsignalized crosswalks were performed.
PL
W pracy przestawiono analizę strat czasu przejazdu pojazdów spowodowane przez przejścia dla pieszych na ulicach jednokierunkowych. Badania obejmowały trzy różne lokalizacje przejść względem skrzyżowania: przejście na odcinku ulicy między skrzyżowaniami, przejście w obrębie strefy oddziaływania skrzyżowania oraz przejście w samej strefie skrzyżowania. Wyniki przeprowadzonych badań wykazały, że znaczący wpływ przejścia bez sygnalizacji na korki obserwuje się w odległości 50-100 m od niego. Przeanalizowano zachowanie oraz czas oczekiwania pieszych na takich przejściach. Potwierdzono, że przechodząc przez jezdnię piesi nie korzystają natychmiast z pierwszeństwa przed samochodami. W pracy przedstawiono zależność czasu oczekiwania pieszych na przejściu od natężenia ruchu pojazdów. Na podstawie uzyskanych danych przygotowano model i przeprowadzono symulacje zachowania pieszych na przejściach bez sygnalizacji.
Rocznik
Strony
201--219
Opis fizyczny
Bibliogr. 36 poz., rys., tab.
Twórcy
  • Lviv Polytechnic National University, Transport Technology Department, Lviv, Ukraine
  • Warsaw University of Life Sciences (SGGW), Faculty of Civil and Environmental Engineering, 159 Nowoursynowska St., 02-776 Warsaw, Poland
  • Warsaw University of Life Sciences (SGGW), Faculty of Civil and Environmental Engineering, 159 Nowoursynowska St., 02-776 Warsaw, Poland
autor
  • Lviv Polytechnic National University, Transport Technology Department, Lviv, Ukraine
autor
  • Lviv Polytechnic National University, Transport Technology Department, Lviv, Ukraine
autor
  • Lviv Polytechnic National University, Transport Technology Department, Lviv, Ukraine
  • Warsaw University of Life Sciences (SGGW), Faculty of Civil and Environmental Engineering, 159 Nowoursynowska St., 02-776 Warsaw, Poland
  • Lviv National University of Nature Management (Lviv National Agrarian University), Dublany, Ukraine
  • Lviv National University of Nature Management (Lviv National Agrarian University), Dublany, Ukraine
  • Mykolayiv National Agrarian University, Mykolayiv, Ukraine
Bibliografia
  • 1. Batyrgareieva V.S., Shramko S.S., Samoilova O.M.: Mortality and injury in Ukraine as a result of traffic accidents in measuring of public health: to the analysis of social-legal and criminological proble
  • 2. Makarova I., Khabibullin R., Pashkevich A., Shubenkova K.: Modeling as a method to improve road safety during mass events. Transportation Research Procedia, 20, 2017, 430-435, DOI: 10.1016/j.trpro.2017.01.070
  • 3. Hughes R.L.: A Continuum Theory for the Flow of Pedestrians. Transportation Research Part B: Methodological, 36, 6, 2002, 507-535, DOI: 10.1016/S0191-2615(01)00015-7
  • 4. Huang L., Wong S.C., Zhang M., Shu C.W., Lam W.H.K.: Revisiting Hughes’ dynamic continuum model for pedestrian flow and the development of an efficient solution algorithm. Transportation Research Part B: Methodological, 43, 1, 2009, 127-141, DOI: 10.1016/J.TRB.2008.06.003
  • 5. Di Francesco M., Markowich P.A., Pietschmann J F., Wolfram M.T.: On the Hughes’ model for pedestrian flow: the one-dimensional case. Journal of Differential Equations, 250, 3, 2011, 1334-1362, DOI: 10.1016/j.jde.2010.10.015
  • 6. Hänseler F.S., Lam W.H., Bierlaire M., Lederrey G., Nikolić M.: A dynamic network loading model for anisotropic and congested pedestrian flows. Transportation Research Part B: Methodological, 95, 2017, 149-168, DOI: 10.1016/j.trb.2016.10.017
  • 7. Carteně A., De Guglielmo M.L., Pascale N.: Congested urban areas with high interactions between vehicular and pedestrian flows: A cost-benefit analysis for a sustainable transport policy in Naples, Italy. The Open Transportation Journal, 12, 2018, 273-288, DOI: 10.2174/1874447801812010273
  • 8. Gu Z., Osaragi T., Lu W.: Simulating pedestrians’ spatio- -temporal distribution in underground spaces. Sustainable Cities and Society, 48, 2019, ID article: 101552, DOI: 10.1016/j.scs.2019.101552
  • 9. Fournier N.: Hybrid pedestrian and transit priority zoning policies in an urban street network: Evaluating network traffic flow impacts with analytical approximation. Transportation Research Part A: Policy and Practice, 152, 2021, 254-274, DOI: 10.1016/j.tra.2021.08.009
  • 10. Shafiei S., Gu Z., Saberi M.: Calibration and validation of a simulation-based dynamic traffic assignment model for a large-scale congested network. Simulation Modelling Practice and Theory. 86, 2018, 169-186, DOI: 10.1016/j.simpat.2018.04.006
  • 11. Zhou J., Wu Y., Mao X., Guo S., Zhang M.: Congestion evaluation of pedestrians in metro stations based on normal-cloud theory. Applied Sciences, 9, 17, 2019, ID article: 3624, DOI: 10.3390/app9173624
  • 12. Wang J., Chen M., Yan W., Zhi Y., Wang Z.: A data-driven approach to estimate the probability of pedestrian flow congestion at transportation bottlenecks. KSCE Journal of Civil Engineering, 23, 1, 2019, 251-259, DOI: 10.1007/s12205-018-0063-1
  • 13. Huang C., Zhang F., Xu Z., Wei J.: The Diverse Gait Dataset: Gait segmentation using inertial sensors for pedestrian localization with different genders, heights and walking speeds. Sensors. 22, 4, 2022, ID article: 1678, DOI: 10.3390/s22041678
  • 14. Shen L., Weng W.: Experimental study on movement characteristics of pedestrians with different speeds. Journal of Statistical Mechanics: Theory and Experiment, 2022, 8, 2022, ID article: 083404, DOI: 10.1088/1742-5468/ac8420
  • 15. Korjagin S., Klachek P.: Innovative development of intelligent transport systems based on biocybernetical vehicle control systems. Transportation Research Procedia, 20, 2017, 326-333, DOI: 10.1016/j.trpro.2017.01.038
  • 16. Fornalchyk Y., Kernytskyy I., Hrytsun O., Royko Y.: Choice of the rational regimes of traffic light control for traffic and pedestrian flows. Scientific Review Engineering and Environmental Sciences, 30, 1, 2021, 38-50, DOI: 10.22630/PNIKS.2021.30.1.4
  • 17. Horbachov P.F., Makarichev O.V., Atamanyuk H.V.: Model of determining the pedestrians’ delay in the transition of streets and roads outside the pedestrian crossing. Automobile Transport, 41, 2017, 82-91
  • 18. Hilevych V.V., Mohyla I.A., Mikhotskyi O.S.: Vyznachennia hranychnykh mezh vlashtuvannia nerehulovanykh pishokhidnykh perekhodiv za kryteriiem zatrymky transportnykh zasobiv. Visnyk Natsionalnoho universytetu Lvivska Politekhnika, Dynamika, mitsnist ta proektuvannia mashyn i pryladiv, 838, 2016, 146-152 (in Ukrainian)
  • 19. Lin Z.Y., Zhang P., Hang H.L.: A dynamic continuum route choice model for pedestrian flow with mixed crowds. Transportmetrica A: Transport Science, 19, 1, 2022, ID article: 2075951, DOI: 10.1080/23249935.2022.2075951
  • 20. Jiang Y., Zhang Y., Lin C., Wu D., Lin C.T.: EEG-based driver drowsiness estimation using an online multi-view and transfer TSK fuzzy system. IEEE Transactions on Intelligent Transportation Systems, 22, 3, 2020, 1752-1764, DOI: 10.1109/TITS.2020.2973673
  • 21. Weijermars W., Bos N., Schoeters A., Meunier J.C., Nuyttens N., Dupont E., Machata K., Bauer R., Perez K., Martin J.L., Johansson H., Filtness A., Brown L., Thomas P.: Serious road traffic injuries in Europe, lessons from the EU research project SafetyCube. Transportation Research Record, 2672, 32, 2018, 1-9, DOI: 10.1177/0361198118758055
  • 22. Wang Y., Shen B., Wu H., Wang C., Su Q., Chen W.: Modeling illegal pedestrian crossing behaviors at unmarked mid-block roadway based on extended decision field theory. Physica A: Statistical Mechanics and its Applications, 562, 2021, ID article: 125327, DOI: 10.1016/j.physa.2020.125327
  • 23. Hu L., Ou J., Huang J., Wang F., Wang Y., Ren B., Peng H., Zhou L.: Safety evaluation of pedestrian-vehicle interaction at signalized intersections in Changsha, China. Journal of Transportation Safety & Security, 14, 10, 2022, 1750-1775, DOI: 10.1080/19439962.2021.1960662
  • 24. Szagała P., Olszewski P., Czajewski W., Dąbkowski P.: Active Signage of Pedestrian Crossings as a Tool in Road Safety Management. Sustainability, 13, 16, 2021, ID article: 9405, DOI: 10.3390/su13169405
  • 25. Olszewski P., Dąbkowski P., Szagała P., Czajewski W., Buttler I.: Surrogate safety indicator for unsignalised pedestrian crossings. Transportation research part F: traffic psychology and behaviour, 70, 2020, 25-36, DOI: 10.1016/j.trf.2020.02.011
  • 26. Zhang C., Chen F., Wei Y.: Evaluation of pedestrian crossing behavior and safety at uncontrolled mid-block crosswalks with different numbers of lanes in China. Accident Analysis & Prevention, 123, 2019, 263-273, DOI: 10.1016/j.aap.2018.12.002
  • 27. Forde A., Daniel J.: Pedestrian walking speed at un-signalized midblock crosswalk and its impact on urban street segment performance. Journal of traffic and transportation engineering (English edition), 8, 1, 2021, 57-69, DOI: 10.1016/j.jtte.2019.03.007
  • 28. Song J., Qiu Z., Ren G., Li X.: Prediction of pedestrian exposure to traffic particulate matters (PMs) at urban signalized intersection. Sustainable Cities and Society, 60, 2020, 102153, DOI: 10.1016/j.scs.2020.102153
  • 29. Stipancic J., Miranda-Moreno L., Strauss J., Labbe A.: Pedestrian safety at signalized intersections: Modelling spatial effects of exposure, geometry and signalization on a large urban network. Accident Analysis & Prevention, 134, 2020, ID article: 105265, DOI: 10.1016/j.aap.2019.105265
  • 30. Sun X., Lin K., Wang Y., Ma S., Lu H.: A study on pedestrian-vehicle conflict at unsignalized crosswalks based on game theory. Sustainability, 14, 13, 2022, ID article: 7652, DOI: 10.3390/su14137652
  • 31. Santhosh A., Sam E., Bindhu B.K.: Pedestrian accident prediction modelling – A case study in Thiruvananthapuram City. In: Mathew T.V., Joshi G.J., Velaga N.R., Arkatkar S. (eds): Transportation Research, 637-645, Springer, Singapore, DOI: 10.1007/978-981-32-9042-6_50
  • 32. Zhao P., Ma J., Xu C., Zhao C., Ni Z.: Research on the safety of the left hard shoulder in a multi-lane highway based on safety performance function. Sustainability, 14, 22, 2022, ID article: 15114, DOI: 10.3390/su142215114
  • 33. Chowdhury T.U., Park P.Y., Gingerich K.: Estimation of appropriate acceleration lane length for safe and efficient truck platooning operation on freeway merge areas. Sustainability, 14, 19, 2022, ID article: 12946, DOI: 10.3390/su141912946
  • 34. Beza A.D., Maghrour Zefreh M., Torok A.: Impacts of different types of automated vehicles on traffic flow characteristics and emissions: a microscopic traffic simulation of different freeway segments. Energies, 15, 18, 2022, ID articles: 6669, DOI: 10.3390/en15186669
  • 35. Li L.: MATLAB User Manual. The MathWorks, Natick, 2001
  • 36. Gasz K., Kruszyna M.: Analyses of pedestrian entry – process to pedestrians crossing. Roads and Bridges - Drogi i Mosty, 3, 2, 2004, 41-64 (in Polish)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-68e0e9c0-5060-4fea-89c4-e9612f72ffac
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