An adaptive freeway traffic state estimator

  • Authors:

  • Yibing Wang;Markos Papageorgiou;Albert Messmer;Pierluigi Coppola;Athina Tzimitsi;Agostino Nuzzolo

  • Affiliations:

  • Institute of Transport Studies, Department of Civil Engineering, Monash University, VIC 3800, Australia;Dynamic Systems and Simulation Laboratory, Department of Production Engineering and Management, Technical University of Crete, 73100 Chania, Greece;Groebenseeweg 2, D-82402, Seeshaupt, Germany;Department of Civil Engineering, "Tor Vergata" University of Rome, Rome, Italy;Dynamic Systems and Simulation Laboratory, Department of Production Engineering and Management, Technical University of Crete, 73100 Chania, Greece;Department of Civil Engineering, "Tor Vergata" University of Rome, Rome, Italy

  • Venue:
  • Automatica (Journal of IFAC)
  • Year:
  • 2009

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Abstract

Real-data testing results of a real-time nonlinear freeway traffic state estimator are presented with a particular focus on its adaptive features. The pursued general approach to the real-time adaptive estimation of complete traffic state in freeway stretches or networks is based on stochastic nonlinear macroscopic traffic flow modeling and extended Kalman filtering. One major innovative aspect of the estimator is the real-time joint estimation of traffic flow variables (flows, mean speeds, and densities) and some important model parameters (free speed, critical density, and capacity), which leads to four significant features of the traffic state estimator: (i) avoidance of prior model calibration; (ii) automatic adaptation to changing external conditions (e.g. weather and lighting conditions, traffic composition, control measures); (iii) enabling of incident alarms; (iv) enabling of detector fault alarms. The purpose of the reported real-data testing is, first, to demonstrate feature (i) by investigating some basic properties of the estimator and, second, to explore some adaptive capabilities of the estimator that enable features (ii)-(iv). The achieved testing results are quite satisfactory and promising for further work and field applications.