NDLI: Regression-based parking space availability prediction for the Ubike system

Content Provider	IET Digital Library
Author	Leu, Jenq Shiou Zhu, Zhe Yi
Abstract	Numerous vehicles exist worldwide such as cars, motorcycles and bicycles. Although parking for such vehicles is available in many places, parking problems still always exist, such as full lots or a lack of lots. Commuters seeking a parking space expend time when spaces are occupied, and resources are wasted when parking spaces are empty. On the other hand, biking is a green vehicle in a fuel-shortage situation and also a good exercise for people. The Ubike system is a popular short-distance transit vehicle system in Taipei City that also has the parking problem. Therefore, this study uses two common regression schemes – linear regression and support vector regression (SVR) to predict the number of bicycles in Ubike stations to determine the number of available parking spaces. It also uses the proportional selection method to increase accuracy and reduce training time for SVR. Some evaluations are conducted to validate the feasibility of the two regression-based service availability prediction schemes for the Ubike system.
Starting Page	323
Ending Page	332
Page Count	10
ISSN	1751956X
Volume Number	9
e-ISSN	17519578
Issue Number	Issue 3, Apr (2015)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-its/9/3
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-its.2014.0094
Journal	IET Intelligent Transport Systems
Publisher Date	2014-09-23
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Bicycles Fuel-shortage Situation Green Vehicle Knowledge Engineering Technique Linear Regression Scheme Parking Space Proportional Selection Method Regression Analysis Regression-based Parking Space Availability Prediction Regression-based Service Availability Prediction Scheme Short-distance Transit Vehicle System Statistics Support Vector Machine Support Vector Regression Scheme SVR Accuracy Enhancement SVR Scheme SVR Training Time Reduction Taipei City Traffic Engineering Computing Ubike Stations Ubike System Vehicle Parking Problem
Content Type	Text
Resource Type	Article
Subject	Law Transportation Environmental Science Mechanical Engineering

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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