Intelligent Transport Greener Future 2025

When looking at global freight sector CO2 emissions as a whole, road transport (trucking) contributes nearly 70%, ships (maritime services) contribute 20%, while aviation and rail each accounts for just 5% of freight emissions.9 Therefore meaningful reductions in emissions at a modal level attributed to AI investments could have a notably different magnitude of impact at the overall freight sector level. While improvements can be amplified through sector-wide collaboration, individual companies can implement these changes independently and benefit from cost reductions. For example, in the US, inefficiencies in dwell time during loading and unloading cost the trucking industry approximately $3.6 billion in direct costs and $11.5 billion in productivity in 2023.10 Incremental improvements may help drive financial gains alongside emissions savings. The scale of downtime costs alone demonstrates the potential cumulative impact of operational efficiency initiatives driven by AI. Road transport, responsible for around 70% of global freight logistics emissions, has the potential to benefit from improvements across all four areas outlined in Figure 2.11 These operational efficiency gains could have a disproportionate impact on the profitability and sustainability of road freight transportation. In terms of the other freight transportation modes, aviation already leverages technology for route optimization, thereby limiting the additional operational efficiency gains compared to road transport. Optimizing shipping routes involves significant coordination and, among other things, includes avoiding the policy of “sail fast then wait” at ports or congested bottlenecks. For rail freight the gains could also be meaningful, especially across predictive maintenance, scheduling and reliability. In the US, inefficiencies in dwell time during loading and unloading cost the trucking industry approximately $3.6 billion in direct costs and $11.5 billion in productivity in 2023. Operational efficiency #1: dwell time optimization 1.1 Dwell times refer to the periods when vehicles, drivers or goods are stationary and not actively engaged in transportation or delivery activities. These idle periods can occur during various stages of logistics operations, such as waiting for loading or unloading, handling items or during other delays. Extended dwell times are a source of unnecessary fuel consumption (and therefore emissions) across the transportation sector. In the US, heavy-duty trucks idling during rest periods emit an estimated 11 million tonnes of CO2 per year, equal to the annual emissions of a small European country such as Estonia.12 AI-powered technologies may offer solutions that enable real-time visibility, tracking and optimized scheduling and planning that can reduce dwell time. Furthermore, dwell time optimization is part of a larger momentum for companies and start-ups that are investing in real time visibility platforms (RTVPs) that use AI to combine dwell time minimization with route optimization across networks. For example, in airlines, AI can potentially help optimize airport operations to reduce wait times for planes and improve auxiliary power unit (APU) efficiency to reduce the fuel burn rates when planes are stationary. We use AI to analyse traffic patterns and optimize loading and unloading schedules at the port, reducing idle times and optimizing space usage. Effective algorithms include reinforcement learning for dynamic decision-making and predictive analytics to forecast peak traffic periods. We collect data from sensors, traffic information systems and terminal operations to create accurate models of traffic flow and container movement. This helps reduce waiting times and increases the overall efficiency of our port operations. Hermann Grünfeld, Head of Traffic Management, Hamburg Port Authority11 million tonnes of CO2 per year emitted by heavy-duty trucks idling during rest periods in the US.% global freight sector CO2 emissions, by mode of transport Road: 70% Ships: 20% Aviation: 5% Rail: 5% Intelligent Transport, Greener Future: AI as a Catalyst to Decarbonize Global Logistics 11