Investigating e-scooters idle time patterns: A survival analysis approach to understand availability

E-scooters have emerged as a popular means of commuting, specifically for short trips, within urban environments. Ensuring the availability of e-scooters within a shared fleet system is crucial for providing convenient services. However, increasing demand and service areas make it challenging to keep e-scooters available based on when and where users want to use them. This study aims to investigate the factors affecting e-scooter availability by specifically studying their idle patterns. Idle time refers to the duration between a vehicle becoming available for pick-up and being rented. Survival analysis was employed to analyze and visualize the probability of e-scooters remaining idle in a shared network in Louisville, Kentucky. Idle time was found to be influenced by several factors, including time of day, season, pick-up location, and operator. Fall and winter drop-offs have longer idle times despite fewer e-scooters indicating a large drop-off in demand. Morning drop-offs have longer idle times than other times of day. The survival analysis identifies optimal pick-up windows that operators can use to guide rebalancing, stage replacements, plan maintenance and charging, and offer incentives, customizing operations and policies to improve service reliability and efficiency.