Data-Driven Analysis of Bicycle Sharing Systems as Public Transport Systems Based on a Trip Index Classification

Area of Science:

• Urban Mobility Studies
• Transportation Science
• Data Science in Transportation

Background:

• Bicycle Sharing Systems (BSSs) are rapidly expanding in urban environments.
• Traditionally viewed as a last-mile solution for public transport, their full potential is often underestimated.

Purpose of the Study:

• To establish Bicycle Sharing Systems (BSSs) as a public transport system in their own right.
• To develop a mathematical framework for classifying BSS trips into transport or leisure categories.
• To analyze the underlying public transport network formed by BSS usage.

Main Methods:

• Development of a novel 'trip index' using trajectory data to classify BSS usage.
• Creation of a mathematical framework to analyze BSS trip purposes.
• Analysis of BSS shortest paths, accounting for real-world cyclist shortcuts.
• Application of the methodology to empirical data from Madrid's BiciMAD system.

Main Results:

• The 'trip index' effectively distinguishes between transport and leisure BSS trips.
• Transport and leisure trips exhibit distinct statistical and operational characteristics.
• The study identified fundamental user trajectories within the BSS network.
• 90.60% of BiciMAD trips were classified as transport, validating BSSs as public transport.

Conclusions:

• Bicycle Sharing Systems (BSSs) function as a significant public transport mode.
• The developed methodology provides a robust framework for analyzing BSS usage patterns.
• Empirical evidence from BiciMAD supports the classification of BSSs as a primary transport solution.