MSSE Thesis Defense: Shivam Mishra, "Hyperlocal Imbalance in Dockless Bike-Share"

Thursday, April 8, 2021
1:00 p.m.
Online presentation
Shivam Mishra
smishra8@umd.edu

MSSE Thesis Defense

Operational Challenges in Dockless Bike-Share: The case of Hyperlocal Imbalance

1:00–3:00 PM

Zoom meeting: https://umd.zoom.us/j/96976227182

Shivam Mishra

Advisory Committee
Co-advisor, Committee Chair: Dr. Derek Paley
Advisor, Committe member: Dr. Ashish Kabra
Committee member: Dr. Ilya Ryzhov

Abstract
Recent times have seen a shift from traditional docked to dockless bike-sharing systems. It is popular among consumers as it allows flexibility to drop-off bikes anywhere and solves the "last-mile" problem of transportation. While convenient for users, the dockless bike-share system's free-floating model introduces the problem of "hyperlocal imbalance," about which no research is available. The hyperlocal imbalance is the supply-demand disparity created in a small geographical region due to consumer's bias to pick up bikes from some locations compared to others. This paper introduces, demonstrates, and determines the reasons behind the "hyperlocal-imbalance" in dockless-bike-sharing systems.

The study of hyperlocal-imbalance requires access to the fine-grained trip level data, which is not easily accessible to the research community due to privacy or competition issues. To deal with it, in this work, we introduce an algorithm to extract trip-level information from the GBFS feeds, which bike-share companies are obliged to upload as per transportation department regulations across the US. The algorithm is validated against the actual trip data of dockless bikes. It extracts the trip details from the GBFS data with a recall of 77% and precision of 80%.

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