This paper reports on the real-data testing of a real-time adaptive freeway traffic state estimator that is based on macroscopic traffic flow modelling and extended Kalman filtering. The testing intends to demonstrate some main features of the estimator that are partly due to its adaptive capability based on on-line model parameter estimation. These features are (1 ) avoiding off-line model calibration ; (2) adaptation to changing environmental conditions; (3) enabling incident alarms. The reported testing results are quite satisfactory and promising for future applications of the estimator.
An adaptive freeway traffic state estimator and its real-data testing-part II: adaptive capabilities
2005-01-01
525418 byte
Conference paper
Electronic Resource
English
An Adaptive Freeway Traffic State Estimator and Its Real-Data Testing-Part II: Adaptive Capabilities
British Library Conference Proceedings | 2005
|An Adaptive Freeway Traffic State Estimator and Its Real-Data Testing-Part I: Basic Properties
British Library Conference Proceedings | 2005
|