Transition Towards Autonomy: Incremental Cost-Benefit Analysis of Autonomous Hub-to-Hub Freight Transport - A Case Study of DFDS

Abstract

The study investigates the cost-benefits of introducing autonomous trucks, focussing on a stepwise transition across the SAE levels of autonomy. A case study methodology is applied using mixed methods and data triangulation. Real-world operational data from the case company DFDS are combined with academic literature, industry insights, and semi-structured expert interviews. Scenario modelling and quantitative analysis are used to simulate cost impacts at different levels of autonomy. Four cost scenarios are introduced to assess the economic viability of each autonomy level. For levels 1–3, a net-zero cost effect is identified as increased technology investment is balanced by modest operational savings. At levels 4 and 5, significant cost reductions of up to 50% are observed in the optimistic scenario, largely driven by lower driver-to-vehicle ratios and increased vehicle utilisation. In a pessimistic scenario, where labour costs remain unchanged, no significant cost advantage is realised. Regulatory, legal, or technical implementation barriers are not taken into account. Given the rapid evolution of the autonomous vehicle industry, ongoing research and regular updates are essential. In all scenarios, the risk of financial loss from adopting autonomous systems is minimal. Early-stage automation offers cost neutrality with potential upside in improved utilisation. The findings support early market entry strategies, especially for operators seeking competitive advantage through learning and ecosystem integration. This study offers a focused, stepwise analysis of cost development across autonomy levels in contrast to prior research that often treats autonomy as a binary concept. By integrating real-world data with scenario-based modelling, it delivers a transparent and grounded perspective on the economic potential of autonomous freight transport.