Intelligent Management and Artificial Intelligence: Trends, Challenges, and Opportunities, Vol.2

Purpose: This study aims to highlight how GIS can enhance spatial data processing and transport optimization, thereby significantly improving the efficiency of logistics systems. Moreover, it explores the potential of integrating AI to coordinate and automate the use of multiple GIS-based models, supporting intelligent management by enabling transport accessibility analyses. Need for the study: The growing complexity of logistics networks requires intelligent management tools that can process spatial data efficiently and adapt to dynamic transport conditions. There is a need for automated solutions that enhance the speed and accuracy of transport accessibility analyses, especially for intermodal infrastructure planning. Methodology: This paper presents the automation of transport accessibility analysis of intermodal terminals using the Model Builder (MB) tool of ArcGIS Pro software. The study is based on spatial data, including terminal locations and road and rail networks in Poland and Germany. The approach allows for the efficient processing of large data sets and dynamic optimization of transport, considering customizable decision support models. Findings: The results of the research demonstrated the effectiveness of the applied GIS tool in automating the assessment of transport accessibility. The approach allowed faster and more accurate data processing and identification of accessibility to intermodal terminals. Practical Implications: The research can support decision-making processes in developing transport infrastructure and helping improve logistics systems' efficiency. Additionally, the potential integration of AI with GIS enables the creation of more flexible, customized decision-support models.