Research on Travel Route Planning Optimization based on Large Language Model

In a trip planning service, travelers first set a starting point, a destination, and a sequential list of specific points of interest types (e.g., museums, restaurants, and parks). Based on this information, the service searches the spatial database to customize the best travel itinerary for the tourist. However, in previous studies, planners only considered the time factor when designing the optimal route, and failed to fully consider the quality of each point of interest. In this study, we specifically leveraged the capabilities of large language model to parse and respond to complex travel-related user queries. To apply large language model to route planning, we fine-tuned the model to understand geotagging and user travel preferences. We have introduced a novel graph search algorithm combined with large language model output, which optimizes the route search process to provide optimal travel recommendations by taking into account various factors such as distance length, budget constraints, and popularity of tourist attractions. In addition, we have integrated real-time traffic data and historical travel data to further improve the prediction accuracy and application usefulness of the model. In the experimental validation phase, we designed a series of benchmarks to compare the performance of the system with traditional algorithms and other machine learning-based route planning methods. Experimental results show that our model has a significant improvement compared with traditional methods in improving the speed and accuracy of path selection.

1. Introduction

In recent years, the advancement of mobile sensing technology and the widespread popularity of mobile social media have provided a rich resource for a variety of emerging researches due to the massive amount of data generated by people using these services. Diverse location-based services can be provided using a variety of shared data sources, such as GPS tracks of taxis, geotagging and reviews on social media, etc. Among them, travel planning services have become a hot area of research. With more and more travelers choosing to travel alone, travel planning has become one of the most critical and time-consuming preparations before traveling. Before heading to their destination, travelers need to have an in -depth understanding of all the attractions in their destination, filter out the best combination of attractions, and plan an efficient travel route [1]. In doing so, they need to consider the type of attraction, rating, duration of visit, and the order in which they visit different attractions. In addition, the traffic conditions of the route and the overall time required need to be considered to ensure that the planned route meets the time requirements of the trip. Only after taking all these factors into account can tourists determine the most suitable travel route for themselves.