Energy-Efficient Flight Path Optimization: A Review of Wind-Aware Routing, AI Planning, and SAF Integration

Abstract

Decarbonizing commercial aviation requires measures that can be deployed before large-scale fleet renewal, and flight-route optimization is one of the most actionable levers available today. This review examines how wind-aware routing, congestion management, artificial intelligence, and sustainable aviation fuels (SAF) can be combined to reduce fuel use and emissions across different operating contexts. A structured survey of literature published between 2010 and 2024 was conducted using major academic databases and technical-report sources; more than 300 records were screened, and 50 studies with quantitative operational or energy outcomes were retained for detailed analysis. The evidence shows that trajectory optimization commonly delivers about 1-4% fuel savings on long-haul operations, network-level traffic measures contribute roughly 2-5%, and AI-assisted planning can achieve larger reductions when supported by high-quality operational data. Studies involving SAF further indicate that route optimization can amplify efficiency and emissions benefits by matching fuel properties, aircraft operating points, and atmospheric conditions. The review also identifies the main barriers to deployment, including certification of data-driven tools, fragmented governance of airspace data, unequal regional access to digital infrastructure, and limited SAF availability. Overall, the literature indicates that the strongest gains arise from integrated implementation rather than isolated interventions, positioning route optimization as a core component of aviation's broader energy-transition strategy.