An Integrated Network Data Model to Support Multimodal Navigation for Smart Mobility

In modern cities, as transportation options become more diverse, it is becoming more common for individuals to combine different modes of transportation to meet their travel needs. However, existing studies have modeled transfer processes between transportation modes as two-dimensional nodes. This approach has limitations, as it cannot provide route guidance within large three-dimensional spaces, such as complex transfer hubs. In response, this study proposes a network data model that models transfer processes as three-dimensional spatial units. In the proposed model, routes within a transfer space are represented using a transfer network, which incorporates various attributes to reflect the characteristics of the actual transfer space. Furthermore, a logical feature for integrating existing transportation networks with transfer networks is introduced to support connections between networks built in different formats without data conversion. The applicability of the model was verified through experiments conducted near the Gwangmyeong Station. Applying the multimodal routing algorithm, the proposed model generated a seamless route from the origin to the destination. These results demonstrate that the proposed model can serve as a foundation for supporting continuous and personalized route guidance services in real-world multimodal environments.