Improving the Service Quality of Bike Sharing Systems via the Analysis of Real-Time User Data

Walteros, Jose L

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Improving the Service Quality of Bike Sharing Systems via the Analysis of Real-Time User Data

2018-10-25
By Walteros, Jose L

File Language:

English

Details

Creators:

Walteros, Jose L
Corporate Creators:

Transportation Informatics University Transportation Center ; State University of New York at Buffalo. Department of Industrial and Systems Engineering
Corporate Contributors:

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
Subject/TRT Terms:
Resource Type:

Tech Report
Geographical Coverage:

United States
Edition:

Final Sep 1, 2017 – Aug 31, 2018
Corporate Publisher:

Transportation Informatics University Transportation Center
Abstract:

The principal objective of this project is to develop a predictive statistical framework to efficiently estimate the ability of a bike-sharing system to serve incoming bike requests. By mining user data collected from the system’s smartphone app, an operator can utilize the proposed models to predict the likelihood that any potential user, who desires to use the system, decides to do so under the given the system’s conditions the user encounters (e.g., the location from where a bike request originates and its proximity to the nearest available bike, the weather conditions, the time of the day, and the customer profile, among others). The proposed statistical model is coupled with an operational bike redistribution model to analyze the cost-effectiveness of triggering quick bike redistribution tours to raise the service quality of the system to desired levels.
Format:

PDF
Funding:

DTRT13-G-UTC48
Download URL:

https://rosap.ntl.bts.gov/view/dot/63603/dot_63603_DS1.pdf
File Type:

[PDF - 2.10 MB]
Collection(s):

University Transportation Centers
Main Document Checksum:

urn:sha256:392c191dd2552f7be69102743ae8b1b61f091ee2092143e4ca02faa3bf572a5a

File Language:

English

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