Global ocean observing systems utilize autonomous underwater vehicles (AUVs) to monitor coastal ocean conditions. These vehicles collect data while facing challenges of shallow waters, changing currents, and stratification. In addition to these natural challenges, A UV s share the waters with increased marine traffic, leading to potentially catastrophic ship strikes. Autonomous vehicles lack the ability to sense vessels, creating a need for a ship detection system leading to evasive maneuvers. Before vessel avoidance behaviors can be effectively implemented, baseline analysis is needed to understand the proximity of vessels to deployed A UV s. This research examines vessel traffic in New Jersey during an underwater glider mission using Automatic Identification System (AIS) mapped vessel movement, and glider data from Rutgers University. We quantify the probability of vessel co-location with a glider by distance, and vessel characteristics including their type and draft. Results show that most ships were not an immediate threat to the glider, with most in the range of 35–110 km. During the mission, less than 0.6% of ship position reports were within 20 km. Many ships were fishing vessels with a distance over 35 km from the glider. The average ship draft was 8 m with a maximum of 19 m. While most vessels were found beyond 35 km of the glider, there was a small but significant number of vessels that could be avoided if the glider were equipped with a ship detection system to make evasive actions.
Dodging Ships: Is New Jersey Vessel Traffic a Threat to Underwater Gliders?
2023-09-25
1304523 byte
Conference paper
Electronic Resource
English
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