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Estimation of the bus delay at the stopping point on the base of traffic parameters

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Contemporary methods of spatial planning of urban transport systems provide for designers enough opportunities in selecting the placement of stopping points for public transport. However in every city there exist very intense sections of the road network with a small width of the roadway. In these sections there is no opportunity to allocate special lanes for public transport. If the stop pockets on such street exist, there appear traffic conflicts when buses depart from the stopping point. Authors propose theoretical model for estimation of the bus delay at the stopping point on the base of traffic parameters. Use of the proposed model allows reducing amount of field surveys while grounding the decisions about rational variant of allocation of the bus stopping points. The paper describes some experimental results obtained with the use of the proposed model while field surveys at the most loaded streets in the central part of Kharkiv (Ukraine).
Rocznik
Strony
15--25
Opis fizyczny
Bibliogr. 21 poz., rys., tab., wykr.
Twórcy
autor
  • Kharkiv National Automobile and Highway University, Transport Systems Department, Kharkiv, Ukraine, gorbachev_pf@mail.ru
autor
  • Kharkiv National Automobile and Highway University, Transport Systems Department, Kharkiv, Ukraine, naumov.vs@gmail.com
autor
  • Kharkiv National Automobile and Highway University, Transport Systems Department, Kharkiv, Ukraine, forgemest@ukr.net
Bibliografia
  • [1] BANDO, M., HASEBE, K., NAKAYAMA, A., SHIBATA, A. and SUGIYAMA, Y., 1994. Structure stability of congestion in traffic dynamics. Japan Journal of Industrial and Applied Mathematics, 11(2), pp. 203-223.
  • [2] BANDO, M., HASEBE, K., NAKAYAMA, A., SHIBATA, A. and SUGIYAMA, Y., 1995. Dynamical model of traffic congestion and numerical simulation. Physical Review E, 51(2), pp. 1035-1042.
  • [3] BLEILE, T., 1997. Traffic simulation supporting urban control system development, Mobility for Everyone: 4th World Congress on Intelligent Transport Systems (21-24 October 1997). 1997, Berlin: ITS Congr. Association, pp. 318.
  • [4] CASCETTA, E., 2013. Transportation systems engineering: theory and methods. New York: Springer Science & Business Media.
  • [5] CHANDLER, R.E., HERMAN, R. and MONTROLL, E.W., 1958. Traffic dynamics: studies in car following. Operations research, 6(2), pp. 165-184.
  • [6] GAZIS, D.C., HERMAN, R. and ROTHERY, R.W., 1961. Nonlinear follow-the-leader models of traffic flow. Operations research, 9(4), pp. 545-567.
  • [7] GIPPS, P.G., 1981. A behavioural car-following model for computer simulation. Transportation Research Part B: Methodological, 15(2), pp. 105-111.
  • [8] HADIUZZAMAN, M. and QIU, T.Z., 2013. Cell transmission model based variable speed limit control for freeways. Canadian Journal of Civil Engineering, 40(1), pp. 46-56.
  • [9] HELBING, D. and TILCH, B., 1998. Generalized force model of traffic dynamics. Physical Review E, 58(1), pp. 133-138.
  • [10] KESTING, A., TREIBER, M. and HELBING, D., 2010. Enhanced intelligent driver model to access the impact of driving strategies on traffic capacity. Philosophical transactions.Series A, Mathematical, physical, and engineering sciences, 368(1928), pp. 4585-4605.
  • [11] KRAUSS, S., WAGNER, P. and GAWRON, C., 1996. Continuous limit of the Nagel-Schreckenberg model. Physical Review E, 54(4), pp. 3707-3712.
  • [12] KRAUSS, S., WAGNER, P. and GAWRON, C., 1997. Metastable states in a microscopic model of traffic flow. Physical Review E, 55(5), pp. 5597-5602.
  • [13] KURZHANSKIJ, A.A., KURZHANSKIJ, A.B. and VARAJA, P., 2010. Rol makromodelirovanija v aktivnom upravleniji transportnoj setju. Trydy MFTI, 2/4(8), pp. 100-118.
  • [14] LIEBNER, M., BAUMANN, M., KLANNER, F. and STILLER, C., 2012. Driver intent inference at urban intersections using the intelligent driver model, Intelligent Vehicles Symposium (IV) 2012, IEEE, pp. 1162-1167.
  • [15] NAGEL, K. and HERRMANN, H.J., 1993. Deterministic models for traffic jams. Physica A: Statistical Mechanics and its Applications, 199(2), pp. 254-269.
  • [16] NAGEL, K. and SCHRECKENBERG, M., 1992. A cellular automaton model for freeway traffic. Journal de physique I, 2(12), pp. 2221-2229.
  • [17] NEWELL, G.F., 1961. Nonlinear effects in the dynamics of car following. Operations research, 9(2), pp. 209-229.
  • [18] PIPES, L.A., 1953. An operational analysis of traffic dynamics. Journal of Applied Physics, 24(3), pp. 274-281.
  • [19] REUSCHEL, A., 1950. Fahrzeugbewegungen in der Kolonne. Osterreichisches Ingenieur Archiv, 4, pp. 193-215.
  • [20] SUMALEE, A., ZHONG, R., PAN, T. and SZETO, W., 2011. Stochastic cell transmission model (SCTM): A stochastic dynamic traffic model for traffic state surveillance and assignment. Transportation Research Part B: Methodological, 45(3), pp. 507-533.
  • [21] TOMER, E., SAFONOV, L. and HAVLIN, S., 2000. Presence of many stable nonhomogeneous states in an inertial car-following model. Physical Review Letters, 84(2), pp. 382-385.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-36408a18-a18d-4ef7-a430-984ad88c88d0
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