Intelligent Applications and Practical Research of GPT-4o in Self-Guided Tour Route Planning

Abstract

The rapid evolution of Artificial Intelligence (AI) has significantly transformed the tourism industry, particularly in self-guided tour planning. This study explores the application of GPT-4o, an advanced AI model, in designing intelligent and adaptive travel itineraries. Traditional itinerary planning faces several challenges, including time-consuming research, lack of flexibility, and overwhelming information overload. AI-powered solutions, particularly GPT-4o, offer a transformative alternative by integrating real-time data analysis, multimodal processing, and personalized recommendations to enhance self-guided travel experiences. This paper presents a comprehensive methodology for AI-driven itinerary generation, detailing the integration of GPT-4o with travel APIs (Google Maps, OpenStreetMap, Booking.com, and real-time transport data) to optimize route planning dynamically. A case study in Kyoto, Japan was conducted, comparing AI-generated itineraries with human-crafted travel plans across four distinct traveler personas: budget traveler, cultural explorer, food enthusiast, and adventure seeker. The results highlight GPT-4o’s efficiency, adaptability, and personalization capabilities, while also acknowledging limitations in local cultural insights and spontaneous human decision-making. Future prospects of AI-driven tourism are explored, including the integration of AR/VR previews, smart city applications, and AI-based crowd management to enhance sustainable tourism practices. Ethical concerns, such as data privacy, algorithmic biases, and AI’s impact on travel spontaneity, are also discussed. The findings indicate that GPT-4o significantly improves travel planning efficiency and adaptability, positioning AI as a cornerstone for the next generation of smart tourism.