An integrated framework for AI-driven green road development in Thailand’s tourism corridors: A mixed-methods approach to energy reduction and sustainability

Thailand’s position as a global tourism leader is intrinsically linked to its transportation infrastructure, which simultaneously fuels economic growth and contributes significantly to the nation’s carbon footprint. Despite ambitious national climate targets, a considerable policy-implementation gap persists, particularly in addressing the lifecycle environmental impacts of road infrastructure itself. This paper proposes a novel, integrated framework to bridge this gap by facilitating the systematic development of “Green Tourism Roads”. The framework is composed of three core components: (1) a quantitative assessment tool, the Thai Tourism Green Road Index (TTGRI), adapted from international best practices to align with Thailand’s specific policy goals; (2) a qualitative validation methodology based on structured stakeholder engagement to ensure practical relevance; and (3) a conceptual architecture for an AI-powered Decision Support System (DSS) that uses genetic algorithms and machine learning to optimize road design for both sustainability and lifecycle cost. A mixed-methods approach is designed to operationalize this framework. To demonstrate its utility, a simulated case study applied to the Mae Hong Son Loop indicates that an AI-optimized Green Road scenario can achieve a “Gold” certification level on the TTGRI, reduce lifecycle Global Warming Potential by over 30%, and lower the 50-year lifecycle cost compared to a business-as-usual approach, despite a modest increase in initial investment. The principal policy recommendations include the formal adoption of a national green road standard based on the TTGRI, the initiation of pilot projects, and investment in institutional capacity building. This research provides a comprehensive, data-driven pathway for Thailand to transform its infrastructure investments into a strategic asset to achieve climate resilience and enhance its sustainable tourism competitiveness.