Abstract:

Bike-sharing systems are increasingly vital for sustainable urban mobility. In Los Angeles, a historically car-dependent city, understanding the spatial and temporal distribution of bike-sharing trips is crucial for optimizing system efficiency (An et al., 2024). This study analyzes bike-sharing usage from 2022 to 2024, focusing on quarterly variations (Q1–Q4) and spatial patterns across neighborhoods. Using spatiotemporal analysis with MGWR models, the research identifies key demand trends and seasonal fluctuations (Shi et al., 2024). Findings offer data-driven insights to enhance station placement, accessibility, and integration into Los Angeles’ transportation network, supporting more efficient and sustainable bike-sharing system planning (Hou et al., 2022).