In recent years, with societal changes, efforts have been made to design public transportation systems, introduce new mobility options, and establish the necessary legal frameworks. As a result, the demand for public transportation and related services is expected to increase in the future, which also suggests a growing demand for transfer search services. Previous studies have shown that, in addition to the aforementioned factors, “transfer resistance” also influences travel route selection. Therefore, this study aims to organize and analyze the contributing factors of transfer resistance, and conduct a simulation of travel route selection based on the model created using these results, in an attempt to provide travel route suggestions that take into account personal preferences. First, a survey was conducted among public transportation users, and the factors contributing to transfer resistance were organized and analyzed through discrete kernel density estimation and clustering using k-means. Next, a travel route selection simulation was designed, with Shinjuku Station as the origin and Tokyo Skytree as the destination. Then, based on the travel route selection model that includes factors contributing to transfer resistance, a virtual experiment was conducted where agents were asked to select travel routes. The study revealed the following findings: The factors that strongly influence transfer resistance are the barrier-free facilities at transportation hubs and the comfort of waiting areas. In the model of this study, when there is no extreme preference, the travel routes selected by agents are common; when there is an extreme preference, agents tend to choose their own unique routes. Based on these findings, it is believed that providing travel route suggestions based on personal preferences can contribute to improving the satisfaction of the minority. These results contribute to providing travel route suggestions that take personal preferences into account.