15 Dec 2023

Ranking Ports by Vessel Demand for Depth

Abstract: The US Army Corps of Engineers (USACE) traditionally uses two metrics to evaluate the maintenance of coastal navigation projects: tonnage at the associated port (representing relative importance) and the controlling depth in the channel (representing operating condition). These are incorporated into a risk-based decision framework directing funds where channel conditions have deteriorated and the disrupted tonnage potential is the highest. However, these metrics fail to capture shipper demand for the maintained depth service provided by the USACE through dredging. Using automatic identification system (AIS) data, the USACE is pioneering new metrics describing vessel demand for the channel depth, represented by vessel encroachment volume (VEV). VEV describes the volume of the hull intruding into a specified clearance margin above the bed and captures how much vessels use the deepest portions of USACE-dredged channels. This study compares the VEV among 13 ports over 4 years by combining AIS, tidal elevations, channel surveys, and sailing draft. The ports are ranked based on the services demanded by their user base to inform the decision framework driving dredge funding allocations. Integrating demand for-depth metrics into the Harbor Maintenance Fee assessment and/or Trust Fund disbursements could alleviate the constitutionality concerns and several criticisms levied against Harbor Maintenance funding.

10 Jun 2022

Inland Waterway Network Mapping of AIS Data for Freight Transportation Planning

Abstract: Travel demand models (TDMs) with freight forecasts estimate performance metrics for competing infrastructure investments and potential policy changes. Unfortunately, freight TDMs fail to represent non-truck modes with levels of detail adequate for multi-modal infrastructure and policy evaluation. Recent expansions in the availability of maritime movement data, i.e. Automatic Identification System (AIS), make it possible to expand and improve representation of maritime modes within freight TDMs. AIS may be used to track vessel locations as timestamped latitude–longitude points. For estimation, calibration and validation of freight TDMs, this work identifies vessel trips by applying network mapping (map-matching) heuristics to AIS data. The automated methods are evaluated on a 747-mile inland waterway network, with AIS data representing 88% of vessel activity. Inspection of 3820 AIS trajectories was used to train the heuristic parameters including stop time, duration and location. Validation shows 84·0% accuracy in detecting stops at ports and 83·5% accuracy in identifying trips crossing locks. The resulting map-matched vessel trips may be applied to generate origin–destination matrices, calculate time impedances, etc. The proposed methods are transferable to waterways or maritime port systems, as AIS continues to grow.