Tracking and predicting barges on inland waterways

Journal Article · Tue Jan 01 04:00:00 EST 2013 · Journal of computing in civil engineering

DOI:https://doi.org/10.1061/(ASCE)CP.1943-5487.0000191· OSTI ID:1122631

Randeniya, Duminda I ^[1]; Hilliard, Michael R ^[1]

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1. ORNL

We present a non-linear, probabilistic prediction model developed and implemented to track spatial location and other navigation characteristics of a barge traveling on the inland waterway system. A pre-filter, to check the validity of the measurements, a non-linear speed estimation process, and a Kalman filter to predict the navigation solution of the barge is developed in this work. Due to the complex dynamics involved in the system, a non-linear stochastic model was developed in state space using system dynamics to represent the process and measurement systems while maintaining the fidelity of an actual system. The algorithm was verified using actual measurements obtained from multiple barges on multiple rivers acquired from different sensors. The results show a reliable and robust prediction algorithm for tracking inland waterway barges.

• Research Organization: Oak Ridge National Laboratory (ORNL)
• Sponsoring Organization: ORNL work for others
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 1122631
• Journal Information: Journal of computing in civil engineering, Journal Name: Journal of computing in civil engineering Journal Issue: 1 Vol. 27; ISSN 0887-3801
• Country of Publication: United States
• Language: English