Estimating Total Demand and Benchmarking Base Price for Student Parking on University Campuses
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 146, Issue 10
Abstract
Most universities limit the number of student parking permits and use their prices to moderate the parking demand. Two critical inputs for implementing such a practice are: (1) the total demand (number of students who will purchase parking permits in a 12-month academic year); and (2) the single, campus-wide base price of student parking permits, benchmarked against other universities. Parking, demographic, and economic statistics were gathered from 208 universities across the United States to calibrate and validate a Beta regression total demand model and a Tobit regression base price model. Three case studies are then presented to illustrate the applications of the models. The first case study compared the models’ solutions against parking management practices at four random selected university campuses; whereas the second case study applied the models to a university to forecast the total demand and the base price in the future. In the third case study, the Monte Carlo simulation technique was adopted to handle uncertainties in the independent variables in the forecasts.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request (spreadsheet of university lists with the parameters, the model details).
Acknowledgments
This work is funded partially by a grant from the US Department of Transportation’s University Transportation Centers Program.
Disclaimer
The contents of this report reflect the views of the authors, who are responsible for the facts and the accuracy of the information presented herein. This document is disseminated in the interest of information exchange. The US Government assumes no liability for the contents or use thereof.
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 146 • Issue 10 • October 2020
Copyright
© 2020 American Society of Civil Engineers.
History
Received: Apr 8, 2020
Accepted: Jun 1, 2020
Published online: Aug 4, 2020
Published in print: Oct 1, 2020
Discussion open until: Jan 4, 2021
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