Large language model-driven multimodal transport route planning methods, systems, media, and electronic equipment for MaaS platforms

Abstract

This application provides a method, system, medium, and electronic device for multimodal transport route planning driven by a large language model for MaaS platforms. The method includes: acquiring basic data based on the MaaS platform to construct descriptive text; parsing and transforming the descriptive text using a preset large language model to obtain multidimensional decision parameters; performing logical verification on the multidimensional decision parameters based on a preset topology to obtain target parameters, the target parameters including standardized calculation parameters required for the route; globally optimizing the target parameters based on a preset target collaborative constraint model to obtain the optimal solution; and converting the data content corresponding to the optimal solution into a natural language description using the large language model and outputting it. This application improves the accuracy of handling natural language requirements in multimodal transport route optimization scenarios, realizes intelligent route planning, and exhibits excellent robustness and accuracy when handling complex node information and dynamic requirements.

Images