Modeling, Identification, Estimation, and Simulation of Urban Traffic Flow in Jakarta and Bandung
This paper presents an overview of urban traffic flow from the perspective of system theory and stochastic control. The topics of modeling, identification, estimation and simulation techniques are evaluated and validated using actual traffic flow data from the city of Jakarta and Bandung, Indonesia, and synthetic data generated from traffic micro-simulator VISSIM. The results on particle filter (PF) based state estimation and Expectation-Maximization (EM) based parameter estimation (identification) confirm the proposed model gives satisfactory results that capture the variation of urban traffic flow. The combination of the technique and the simulator platform assembles possibility to develop a real-time traffic light controller.
W.Y. Ming, J. Bie and B. van Arem, â€œUser Needs in Green ITS: Results of a Questionnaire Survey and Proposal for Green ITS Design,â€? Inter. J. Intell. Transport. Syst., 10, 47â€“55, 2012. crossref.
Y.B. Wang, M. Papageorgiou, A. Messmer, P. Coppola, A. Tzimitsi and A. Nuzollo, â€œAn adaptive freeway traffic estimator,â€? Automatica, 45(1), 10-24,
L. Mihaylova, R.K. Boel and A. Hegyi, â€œFreeway Traffic Estimation within Particle Filtering Framework,â€? Automatica, 43, 290-300, 2007. crossref.
C.R. Vasquez, H.Y. Sutarto, R.K. Boel and M. Silva, â€œHybrid Petri net model of a traffic intersection in a urban network,â€? IEEE Multi-conference on Systems and Control, Yokohama, Japan, Sept 2010. crossref.
J.D. Hamilton, â€œAnalysis of time series subject to change in regime,â€? Journal of Econometrics, 45,39-70,1990. crossref.
S. Tafazoli and X. Sun, â€œHybrid system state tracking and fault detection using particle filter,â€? IEEE Trans. on Control System
Technology, 14(6), 2006. crossref.
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