Usage Patterns of Free-floating Carsharing Members

Abstract

Shared vehicles are a building block of sustainable transport systems, because they have the potential to reduce private vehicle ownership rates, vehicle miles travelled and to increase vehicle fleet efficiency. Although both supply and demand of carsharing have increased in recent years, alongside research efforts on the topic, little is known about usage patterns of carsharing members. Yet, we need to consider carsharing usage patterns as a whole to find out who is currently using carsharing and what their usage behavior is, in order to increase demand even further in the future. This paper presents the results of a user-focused cluster analysis which we applied to identify distinctive usage patterns of free-floating carsharing users in Karlsruhe, Germany. The results of a k-means cluster analysis conducted using booking data provided by a free-floating carsharing provider show partitions of members based on their travel patterns. While freefloating and station-based carsharing present an overlap in usage patterns to some extent, the two systems generally supplement each other well, leading to a more comprehensive supply of vehicles, mitigating needs of private vehicle ownership.