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arXiv · 2409.08069

TravelAgent: An AI Assistant for Personalized Travel Planning

Aili Chen·Xuyang Ge·Ziquan Fu·Yanghua Xiao·Jiangjie Chen
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Abstract

As global tourism expands and artificial intelligence technology advances, intelligent travel planning services have emerged as a significant research focus. Within dynamic real-world travel scenarios with multi-dimensional constraints, services that support users in automatically creating practical and customized travel itineraries must address three key objectives: Rationality, Comprehensiveness, and Personalization. However, existing systems with rule-based combinations or LLM-based planning methods struggle to fully satisfy these criteria. To overcome the challenges, we introduce TravelAgent, a travel planning system powered by large language models (LLMs) designed to provide reasonable, comprehensive, and personalized travel itineraries grounded in dynamic scenarios. TravelAgent comprises four modules: Tool-usage, Recommendation, Planning, and Memory Module. We evaluate TravelAgent's performance with human and simulated users, demonstrating its overall effectiveness in three criteria and confirming the accuracy of personalized recommendations.

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Aili Chen, Xuyang Ge, Ziquan Fu, Yanghua Xiao, Jiangjie Chen. 2024-09-12. TravelAgent: An AI Assistant for Personalized Travel Planning. https://arxiv.org/abs/2409.08069

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