Work

Making sense of data: leveraging AI to empower data-driven decision making in public transport

Year: 2025

Type: article

Abstract: Public transport authorities collect vast amounts of data on travel behavior. However, effectively utilizing this data is challenging. This paper addresses this challenge by presenting an AI-based data management tool prototype designed to support public transport authorities in making better use of their data. The tool leverages large language models (LLMs) and retrieval-augmented generation (RAG) to provide functionalities such as uploading data, querying, summarizing, and chatbot interaction. The paper discusses the development process, user needs and challenges identified, and the findings from user evaluations. The evaluation results indicate that the tool has the potential to improve data accessibility, user understanding of travel patterns, and collaboration among stakeholders, while acknowledging the need for user awareness of the tool’s limitations.

Source: Transportation research procedia

DOI: 10.1016/j.trpro.2025.04.087

Authors: Maria Ulan, Mikael Söderman

Institution: RISE Research Institutes of Sweden

Language: English

Topic: Transportation Planning and Optimization

Subfield: Transportation

Field: Social Sciences

Domain: Social Sciences

SDGs: Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: diamond

Funder: VINNOVA