A predictive methodology for vessel travel times: An application on the Gulf Intracoastal Waterway (GIWW)

Abstract

The Gulf Intracoastal Waterway (GIWW) is one of the most highly used corridors in the U.S. inland waterway commerce network, necessitating accurate travel time estimation for operational planning (departure times and achieve on-time arrivals). This paper addresses the significant need for assessing GIWW travel times and proposes a two-phase approach utilizing Automatic Identification System (AIS) data and other data sets.

In the initial phase, forecasting models and event evaluation methods are applied to predict travel times based on specific events, and in the second phase, the impact of different variables on system performance is investigated.

The results indicate that sample count (completed trips through a link) does not significantly influence travel time across any link. The statistical analysis highlights two critical conditions affecting travel time: dredging and shoaling. Furthermore, the analysis presented in this paper estimates the expected magnitude of these events and their probability of occurrence.

By applying the proposed methodology to estimate travel times of the GIWW, this paper contributes to the enhancing travel time estimation tools, offering valuable information for decision-makers, operators, and users navigating this crucial waterway.