Spatiotemporal Dynamics and Behavioral Patterns of Micro-Electric Vehicle Trips for Sustainable Urban Mobility

This study investigates the spatiotemporal characteristics and travel patterns of micro-electric vehicles (micro-EVs) by analyzing real-world trip data collected over three years from shared micro-EV services operating in three regions of South Korea. Individual trips were extracted from GPS-based trajectory data, and a network-based detour ratio was introduced to capture non-linear trip characteristics. In addition, a hierarchical clustering analysis was applied to identify heterogeneous micro-EV trip patterns. The results show that micro-EVs are predominantly used for short-distance urban trips, while a smaller but behaviorally distinct subset of trips demonstrates their capacity to support medium-distance travel under specific functional contexts. The clustering analysis identified six distinct trip pattern groups, ranging from dominant short-distance routine travel to less frequent patterns associated with adverse weather conditions and extreme detouring behavior. Overall, the findings suggest that micro-EVs function as a complementary urban mobility mode, primarily supporting localized travel while selectively accommodating extended-range and specialized trips. From a sustainability perspective, these findings highlight the role of micro-EVs as energy-efficient, low-emission alternatives to conventional passenger vehicles for short- and medium-distance urban trips. By empirically identifying heterogeneous and long-tailed micro-EV travel patterns, this study provides practical insights for sustainable urban mobility design and environmentally responsible transportation policies.