Sustainable truck platooning operations in maritime shipping: A data-driven approach

Abstract

In liner shipping, stakeholders are increasingly committed to adopting autonomous and environmentally friendly transportation solutions, especially for truck operations managing container transfers. Beyond reducing labor costs, truck platooning technology—which enables autonomous trucks to operate in close formations, thereby significantly decreasing fuel consumption—promises to revolutionize fleets involved in maritime container transport. However, the potential of these benefits hinges on the process of developing and implementing optimization plans that address the specific challenges of container logistics, particularly in integrating truck platooning plans. In response to this need, this study extends the traditional instant-dispatch strategy by proposing a novel, data-driven dispatch strategy. We develop algorithms for both models and conduct extensive experiments focusing on truck operations for sea freight containers. Our findings reveal significant advantages of the data-driven dispatch strategy: it substantially reduces the total costs and fuel consumption associated with truck deliveries compared to the instant-dispatch strategy.