Abstract
Recent years have seen a tremendous interest world wide in the use of microsimulation techniques to model traffic in congested road networks. This interest is particularly associated with the development of real-time, high-tech based traffic management and control strategies that react to the highly dynamic and variable nature of traffic conditions and driver behaviour. This paper introduces the DRACULA dynamic traffic network model, with the main focus on its traffic microsimulation component. The paper describes the model’s theoretical and behavioural foundations, and presents illustrative examples of applying the model in the evaluation of real-time management strategies. Our experience shows that this is a particularly suitable framework for the realistic modelling of real-time technological strategies.
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References
Altruist, S., Hyden, C. & Risser, R. (1991). Use of speed limiters in cars for increased safety and a better environment, Transport Research Record, 1318, pp34–39.
Barcelo, J., Ferrer, J., Grau, R., Florian, M. and Chabini, E. (1995). A route based version of the AIMSUN2 microsimulation model, 2 nd World Congress on ITS, Yokohama.
Ben-Akiva, M., De Palma, A. and Kanaroglou, P. (1986). Dynamic model of peak period traffic congestion with elastic arrival rates. Transportation Science, 20(2), pp 164–181.
Cantarella, G.E. and Cascetta, E. (1995). Dynamic process and equilibrium in transportation networks: towards a unifying theory, Transportation Science 29(4), pp305–329.
Edie, L.C. (1961). Following and steady-state theory for non-congested traffic, Oper. Res., 9, pp66–76.
Emmerink, R.H.M., Axhausen, K.W., Nijkamp, P. and Rietveld, P. (1994). Effects of information in road transport networks with recurrent congestion, Transportation, 22, pp21–53.
Emmerink, R.H.M. and Nijkamp, P. (ed.) (1999). Behavioural and Network Impacts of Driver Information Systems, Avebury, Aldershot, UK.
Fellendorf, M., MacAongusa, C. and Pierre, M. (1997). LRT priority within the SCATS environment in Dublin-a traffic flow simulation study, Proc. Urban Transport and the Environment, Computational Mechanics Publications, Oct. 1997.
Gipps, P.G. (1981). A behavioural car-following model for computer simulation,. Transportation Research 15B, pp105–111.
Hu., T.-Y. and Mahmassani, H.S. (1997). Day-to-day evolution of network flows under real-time information and reactive signal control, Transportation Research, 5C, pp51–69.
Hunt, P.B., Robertson, D.I, Bretherton, R.D. and Winton, R.I. (1981). SCOOT — a traffic responsive method of coordinating signals, TRRL Laboratory Report 1014.
ITE (1982). Transportation and Traffic Engineering Handbook, 2nd edition. Institute of Transportation Engineers, Prentice-Hall Inc., Englewood Cliffs, N. J.
Jha M, Madanat S and Peeta S (1999). Perception updating and day-to-day travel choice dynamics in traffic networks with information provision, Transportation Research 6C(3), pp189–212.
Koshi, M., Iwasaki, M. and Ohkura, I. (1983). Some findings and an overview on vehicular flow characteristics, Proc. 8 th International Symposium on Transportation and Traffic Flow Theory (eds. V. Hurdle, E. Hauer, & G. Stuart), pp403–426.
Laird J, Druitt S & Fraser D (1999). Edinburgh city centre: a microsimulation case-study, Traffic Eng. & Contr, 40(2), pp72–76.
Lind, G. (1999). Large-scale testing of intelligent speed adaptation — important evaluation issues, Proc. AET European Transport Conference, Seminar D, Vol P432, pp91–103, Cambridge.
Liu R, Van Vliet D and Watling DP (1995). DRACULA: Dynamic Route Assignment Combining User Learning and microsimul Ation, Proc. PTRC Annual Conference, Seminar E, pp143–152.
Liu R, Clark SD, Montgomery FO and Watling DP (1999). Microscopic modelling of traffic management measures for guided bus operation, Selected Proceedings of 8th World Conference on Transport Research (eds. Oum, TH, Meersman, H & Winkelmans W), Vol 2, 367–380, Elsevier.
Liu R. and Tate J. (2000). Microsimulation modelling of intelligent speed adaptation systems, Proc.European Transport Conference, Cambridge 2000.
Liu, R., Silva, J. and Seco, A. (2002). A bi-modal microsimulation model for the assessment of pedestrian delays and traffic management, Paper submitted to Transportation Research C.
Mahmassani, H.S. and Jayakrishnan, R. (1991). System performance and user response under real-time information in a congested traffic corridor, Transportation Research, 25A, pp293–308.
Mauro, V. (1991). Evaluation of dynamic network control: simulation results using NEMIS urban microsimulator, Transportation Research Board 70th annual meeting, Washington DC.
May, A.D. (1990). Traffic Flow Fundamentals, Prentice Hall, Englewood Cliffis, New Jersey.
May, A.D. and Milne, D.S. (2000). Effects of alternative road pricing systems on network performance, Transportation Research, 34A, pp407–436.
Milne, D.S. (1997). Modelling the Effects of Urban Road User Charging, PhD, University of Leeds.
Nagel, K. and barrett, C.L. (1997). Using microsimulation feed back for trip adaptation for realistic traffic in Dallas, International Journal of Modern Physics C, 8(3), pp505–526.
Nsour S and Santiago A (1994). Comprehensive plane development for testing, calibration and validation of CORSIM, In Proc. of 64 th ITE Annual Transportation Engineers, Dallas, pp486–490.
Oldridge, B. (1990). Electronic road pricing-an answer to traffic congestion?, Proc. Information Technology and Traffic Management, HMSO, London.
Papageorgiou, M., Hadi-Salem, H., Blosseville, J.M. and Bhouri, N. (1989). Modelling and real-time control of traffic flow on the Boulevard Peripherique in Paris, IFAC Control, Computers, Communications in Transportation, Paris, Pergamon, Oxford, pp205–211.
Rossetti, RJF, Bordini, R.H., Bazzan, A.L.C., Bampi, S., Liu, R. and Van Vliet, D. (2002). Using BDI agents to improve driver modelling in a commuter scenario, Trans. Res. 10C, pp47–72.
Quinn, DJ. (1992). A review of queue management strategies, Traffic Eng. & Contr., 33(11), pp600–605.
Van Vliet, D. (1982). SATURN-a modern assignment model, Traffic Eng. & Contr., 23(12), pp578–581.
Vythoulkas, P.C. (1990). A dynamic stochastic assignment model for the analysis of general networks, Transportation Research 24B, pp453–469.
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Liu, R. (2005). The DRACULA Dynamic Network Microsimulation Model. In: Kitamura, R., Kuwahara, M. (eds) Simulation Approaches in Transportation Analysis. Operations Research/Computer Science Interfaces Series, vol 31. Springer, Boston, MA. https://doi.org/10.1007/0-387-24109-4_2
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DOI: https://doi.org/10.1007/0-387-24109-4_2
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