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Modeling of Transport Network Resilience in Gdynia for Disturbing Events

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 897))

Abstract

Traffic accidents or mass events might cause large-scale traffic congestion. It might increase travel times of drivers and produces many social losses. The article will present a proposal of a mathematical model describing the impact of mass events and serious failures of transport infrastructure on the transport network of the city of Gdynia. The model was built using data, obtained from the TRISTAR system, collected during the failure on a street and the Opener event. They were used to estimate the parameters of the model. The use of real data to create a mathematical model that maps traffic situations will enable real reference to the real behaviour of drivers in the analysed area. The article describes the use of the model and presents the method of using a convex combination of two triangular distributions to describe two independent communication peaks. Due to the presence of two independent maxima of functions in the case of the morning and afternoon communication summits, it is not possible to describe this phenomenon with only one function. The critical intersection selected for the model has to meet the daily transport of people using passenger vehicles and is also tailored to the geometric dimension of the trucks. The biggest challenge is to adjust the traffic lights. The signaling is managed by the traffic control center in Gdynia with the implemented intelligent transport system - TRISTAR.

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References

  1. Jamroz, K., Oskarbski, J.: TRISTAR - Trójmiejski Inteligentny System Transportu Aglomeracyjnego. Transport Miejski i Regionalny (2006)

    Google Scholar 

  2. www.opener.pl. Accessed 7 Feb 2018

  3. Smolarek, L., Ziemska, M.: Analysis of the effect of mass events on car traffic in the city in the daily interval. In: 2017 2nd International Conference on System Reliability and Safety (ICSRS 2017), Milan, Italy, pp. 521–525 (2017)

    Google Scholar 

  4. Jamroz, K., Oskarbski, J.: Inteligentny system transportu dla aglomeracji trójmiejskiej. Telekomunikacja i Techniki Informacyjne, nr 1–2 (2009)

    Google Scholar 

  5. https://web.archive.org/web/20140407075018/. Accessed 7 Feb 2018

  6. http://www.asianscientist.com/books/wp-content/uploads/2013/06/5720_chap1.pdf. Accessed 7 Feb 2018

  7. Raghu, N.K., Lawrence, J.F.: Trapezoidal and triangular distributions for Type B evaluation of standard uncertainty. Metrologia 44, 117–127 (2007)

    Article  Google Scholar 

  8. www.ics.uci.edu/~smyth/courses/cs274/notes/EMnotes.pdf. Accessed 7 Feb 2018

  9. D’Lima, M., Medda, F.: A new measure of resilience: an application to the London underground. Transp. Res. Part A 81, 35–46 (2015)

    Google Scholar 

  10. Generalna Dyrekcja Dróg Krajowych i Autostrad, Metoda obliczania przepustowości skrzyżowań z sygnalizacją świetlną. Instrukcja obliczania. Wydawnictwo PiT, Warszawa (2004)

    Google Scholar 

  11. Report, Transport Resilience Review, A review of the resilience of the transport network to extreme weather events, Presented to Parliament by the Secretary of State for Transport by Command of Her Majesty (2014). www.gov.uk/government/publications. Accessed 7 Feb 2018

  12. Hughes, J.F., Healy, K.: Measuring the resilience of transport infrastructure, AECOM New Zealand Ltd, NZ Transport Agency research report 546 (2014). www.nzta.govt.nz

  13. Smoczyński M.: Natężenie nasycenia relacji dla skrzyżowań z sygnalizacją świetlną modelowanych z wykorzystaniem automatów komórkowych., Autobusy: technika, eksploatacja, systemy transportowe, s. 1267—1272, June 2017

    Google Scholar 

  14. BALANCE – intelligent signal control for sustainable road traffic. http://travolution-ingolstadt.de. Accessed 7 Feb 2018

  15. Ziemska, M., Smolarek, L.: Using information collected by weigh in motion for modeling traffic structure of vehicles. Arch. Transp. Syst. Telematics 4, 32–37 (2016). Polish Association of Transport Telematics

    Google Scholar 

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Correspondence to Monika Ziemska .

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Ziemska, M., Smolarek, L. (2018). Modeling of Transport Network Resilience in Gdynia for Disturbing Events. In: Mikulski, J. (eds) Management Perspective for Transport Telematics. TST 2018. Communications in Computer and Information Science, vol 897. Springer, Cham. https://doi.org/10.1007/978-3-319-97955-7_12

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  • DOI: https://doi.org/10.1007/978-3-319-97955-7_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-97954-0

  • Online ISBN: 978-3-319-97955-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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