Currently, a variety of shared mobility services are available. Shared mobility services serve as first/last mile transportation options to enhance personal mobility and improve access to transportation services. Among these shared mobility services, Personal Mobility (PM) is garnering attention due to its potential to address urban traffic issues by offering environmentally friendly benefits such as reducing traffic congestion and facilitating easier parking. Moreover, by solving the first/last mile problem of public transportation and employing a PM-specific algorithm for route guidance, the efficiency and competitiveness of public transportation can be improved. Existing route guidance algorithms do not adequately account for PM-specific characteristics and often direct users along inefficient routes primarily designed for vehicles or public transportation. This study aims to propose an algorithm exclusively tailored for PM and present an efficient path that incorporates PM characteristics. By effectively addressing the first/last mile service for users, this algorithm aims to enhance traffic efficiency and user convenience. In fact, the commuting route around a subway station in Seoul was set as a demonstration area to analyze the mode shift effect of applying the PM application algorithm. through the modal split process of the transportation demand forecasting model. As a result of the analysis, the modal shift to public transportation by applying the PM application algorithm was 269,925 in 2025, and the air pollution reduction benefit was calculated to be 82.85 billion KRW/y. The increased utility of PM can lead to environmental benefits by bolstering the competitiveness and ridership of public transportation. The findings of this study are expected to serve as a quantitative foundation for establishing shared mobility distribution policies aligned with the era of mobility transformation.