Abstract
This study proposes the modified stochastic cell transmission model (M-SCTM), which can be used to apply the conventional SCTM to urban networks. Although SCTM can represent an uncertainty of traffic state and changing travel demand or supply conditions, it has been applied to a freeway or a simple network that has only one origin-destination pair. In M-SCTM, we introduce vehicle agents and their route choice behavior on an urban network for application to more complex urban networks. From the results of an empirical study, we confirm the reproducibility of traffic volume and travel time that are calculated by M-SCTM.
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References
Sumalee, A., Zhong, R., Pan, T., Szeto, W.Y.: Stochastic cell transmission model (SCTM): A stochastic dynamic traffic model for traffic state surveillance and assignment. Transportation Research Part B 45, 507–533 (2011)
Sumalee, A., Pan, T., Zhong, R., Uno, N., Indra-Payoong, N.: Dynamic stochastic journey time estimation and reliability analysis using stochastic cell transmission model: Algorithm and case studies. Transportation Research Part C: Emerging Technologies 35, 63–285 (2013)
Chen, B., Cheng, H.H.: A review of the applications of agent technology in traffic and transportation systems. IEEE Transactions on Intelligent Transportation Systems, 485–497 (2010)
Muñoz, L., Sun, X., Horowitz, R., Alvarez, L.: Traffic Density Estimation with the cell transmission model. In: Proceedings of the American Control Conference, Denver, Colorado, USA, pp. 3750–3755 (2003)
Sun, X., Muñoz, L., Horowitz, R.: Highway Traffic State Estimation Using Improved Mixture Kalman Filters for Effective Ramp Metering Control. In: 42th IEEE Conference on Decision and Control, vol. 6, pp. 6333–6338 (2003)
Zhong, R., Sumalee, A., Pan, T., Lam, W.: Stochastic cell transmission model for traffic network with demand and supply uncertainties. In: Transportmetrica A: Transport Science, P567–P602 (2013)
Greenshields, B.D.: A study of traffic capacity. Highway Research Board 14, 448–477 (1935)
Dijkstra, E.W.: A note on two problems in connexion with graphs. Numerische Mathematik 1, 269–271 (1959)
Traffic Simulation Clearinghouse.: Public Website for Verification Data in Traffic Simulation Clearinghouse, http://www.i-transportlab.jp/bmdata/KichijojiBM/ave-dataset/ave-index.html
Fransson, M., Sandin, M.: Framework for Calibration of a Traffic State Space Model. In: Master of Science in Communication and Transport Engineering, P42–P48 (2012)
Dial, R.B.: A probabilistic multi-path traffic assignment mode1 which obviates path enumeration. Transportation Research 5, 83111 (1971)
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Tokuda, S., Kanamori, R., Ito, T. (2014). Development of Traffic Simulator Based on Stochastic Cell Transmission Model for Urban Network. In: Dam, H.K., Pitt, J., Xu, Y., Governatori, G., Ito, T. (eds) PRIMA 2014: Principles and Practice of Multi-Agent Systems. PRIMA 2014. Lecture Notes in Computer Science(), vol 8861. Springer, Cham. https://doi.org/10.1007/978-3-319-13191-7_13
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DOI: https://doi.org/10.1007/978-3-319-13191-7_13
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13190-0
Online ISBN: 978-3-319-13191-7
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