Similarity measure for station clustering in bike sharing systems
- Resource Type
- Conference
- Authors
- Florian, Horatiu; Pop, Mihai; Avram, Camelia; Astilean, Adina
- Source
- 2020 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR) Automation, Quality and Testing, Robotics (AQTR), 2020 IEEE International Conference on. :1-5 May, 2020
- Subject
- Components, Circuits, Devices and Systems
Computing and Processing
General Topics for Engineers
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Automation
Conferences
Urban areas
Transportation
Clustering algorithms
Time measurement
Planning
bike share systems
clustering
similarity measure
bike availability
- Language
Bike sharing systems are one of the proposed solutions for personal transportation in cities around the world. Clustering is a principal direction for research done on bike sharing systems with the purpose of reducing computational difficulty of problems associated with operating such systems. This paper proposes a new similarity measure for station clustering based on periods of low bike availability. The method described is tested on real world bike share data obtained for Citi Bike in New York. A time-based validation is done for the proposed algorithm.