Indirect observation of rerouting phenomena in traffic networks – case study of Warsaw bridges

• Autorzy: Kucharski R. , Gentile G.

Identyfikatory

DOI

10.5604/08669546.1146996

• Języki publikacji: EN

Abstrakty

EN

In this paper we propose estimation procedure in which traffic flows resulting from rerouting model are matched with traffic flows observed during unexpected events. We show practical value of observing a entire cut-set of the transportation network and propose theoretical closed-form formulation of estimation problem for the rerouting model. We apply proposed framework on field-data from Warsaw bridges to observe rerouting phenomena. Most importantly we observed that: a) around 20% of affected traffic flow reroutes, b) rerouting flows are increasing in time, c) drivers show strategic capabilities, d) and maximize their utility while rerouting. All of the which were hypothesized in Information Comply Model (Kucharski et. al., 2014) and are now supported with field observations.

Słowa kluczowe

EN

traffic events; dynamic traffic; transportation network; rerouting phenomena; traffic management; real-time traffic

PL

zdarzenia drogowe; ruch dynamiczny; sieć transportowa; przekierowania; zarządzanie ruchem

• Wydawca: Warsaw University of Technology, Faculty of Transport
• Czasopismo: Archives of Transport
• Rocznik: 2014
• Tom: Vol. 32, iss. 4
• Strony: 29--41
• Opis fizyczny: Bibliogr. 8 poz., rys., tab., wykr.

Twórcy

autor

Kucharski R.

• University of Technology, Department of Transportation Systems, Cracow, Poland

autor

Gentile G.

• DICEA, Sapienza University of Rome, Rome, Italy

Bibliografia

• [1] Kucharski, R., Gentile, G., Direct observation of rerouting phenomena in traffic networks. Archives of Transport, vol. 30/Issue 2, pp.57-66, 2014.
• [2] Kucharski, R., Gentile, G. & Meschini, L. 2014, Information Comply Model – new model to represent rerouting phenomena in Dynamic Traffic Assignment, 5th International Symposium on Dynamic Traffic Assignment, pages 1-32, Salerno, 2014.
• [3] Corthout, R., Tampère, C.M.J., Immers, L.H. (2009) Marginal Incident Computation : An Efficient Algorithm to Determine Congestion Spillback due to Incidents. Proceedings of the 88th Annual Meeting of the Transportation Research Board, pp.1–22.
• [4] Snowdon,J., Waterson,B., Fangohr H. (2012) Evolution of adaptive route choice behaviour in drivers. UTSG: 44th Annual Conference of the Universities’ Transport Study Group, Aberdeen
• [5] Gao S., Frejinger E., Ben-Akiva M. (2008) Adaptive route choice models in stochastic time-dependent networks. Transporstation Research Record: Journal of TRB.
• [6] Hranac, R., Kwon, J., & Barkley, T. (2011). Leveraging ITS Sensors to Understand Travel Time Reliability. Proceedings of the 2nd Modeling Techniques for ITS Conference, Leuven.
• [7] Lighthill M., Whitham G. (1955) On kinematic waves II: A theory of traffic flow on long crowded roads. Proceedings of Royal Society, vol. 229A, pp. 317-345.
• [8] Gentile G. (2010) The General Link Transmission Model for Dynamic Network Loading and a comparison with the DUE algorithm. (selected papers from the DTA 2008 Conference, Leuven), ed.s L.G.H. Immers, C.M.J. Tampere, F. Viti, Transport Economics, Management and Policy Series, Edward Elgar Publishing, MA, USA.