Case study

Roboat

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The Roboat project, based in Amsterdam, is an initiative aimed at transforming urban waterway transport using fully autonomous boats. Led by the Amsterdam Institute for Advanced Metropolitan Solutions (AMS) and MIT, Roboat has developed AI-powered vessels capable of navigating Amsterdam’s canal network.

Amsterdam's narrow streets and high tourism levels contribute to significant road congestion, which impacts transport efficiency and increases pollution. The city’s expansive canal network offers a potential solution for alleviating traffic, but traditional water transport remains limited in capacity and scope. Amsterdam needed an innovative system to optimize these waterways, reduce road congestion, and support more sustainable, low-emission transportation alternatives.
Roboat's autonomous boats are designed to navigate urban waterways using an advanced AI-powered system. The vessels perform a range of functions, including passenger transport, goods delivery, and waste collection. With AI-driven situational awareness, Roboat can adapt to heavy waterway traffic and changing environmental conditions without human intervention. The boats' modular design also allows for retrofitting on existing vessels, making the solution flexible for various applications in Amsterdam and other European cities.
Implementing the Roboat technology has required navigating several challenges. These include ensuring that the AI system functions effectively in Amsterdam’s busy canals, where waterway congestion is common. Additionally, adapting the technology to comply with European and local regulations has required close collaboration with regulatory bodies. Ensuring reliability and safety in autonomous operation, especially for transporting passengers, has also necessitated rigorous testing and iteration of the AI models.
Roboat has successfully launched its autonomous vessels, with current deployments showcasing their utility for Amsterdam's GVB ferry system, where they assist with situational awareness for skippers. The project has reduced dependency on road-based transport, contributing to a decrease in the carbon footprint associated with city logistics.

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