Volume 2, Issue 1, January 2017, Page: 1-5
Model Construction and Quantitative Analysis of Taxi-Hailing Subsidy Scheme
Jiarui Xing, School Information Science and Technology, Beijing Normal University, Beijing, China
Shuxiao Wang, School Mathematical Science, Beijing Normal University, Beijing Normal University, Beijing, China
Zihao Zheng, School Mathematical Science, Beijing Normal University, Beijing Normal University, Beijing, China
Received: Oct. 25, 2016;       Accepted: Feb. 13, 2017;       Published: Mar. 4, 2017
DOI: 10.11648/j.ajtte.20170201.11      View  1563      Downloads  55
Abstract
The convenient taxi-hailing is a big issue for nearly all cities in China. Striving to ease the taxi-hailing difficulty" as the objective function, the "economic expenditure of the subsidies" as the budget constraints, a more ideal taxi subsidy program and its budget is obtained by solving the conditional extreme value function based on the Lagrange method. The subsidy schemes according to the per mileage subsidy to the taxi driver will be optimal choice in the peak hours/urban center and in the off-peak hours/ urban fringes. Whereas, the subsidy schemes will be the most effective in the off-peak hours/ urban center and in peak hours/urban fringes in the light of the fuel consumption subsidy to the taxi driver. A sensitivity analysis is made for the parameters of model to evaluate its key influencing factors on stability.
Keywords
Budget, Taxi-Hailing Subsidy Scheme, Sensitivity Analysis
To cite this article
Jiarui Xing, Shuxiao Wang, Zihao Zheng, Model Construction and Quantitative Analysis of Taxi-Hailing Subsidy Scheme, American Journal of Traffic and Transportation Engineering. Vol. 2, No. 1, 2017, pp. 1-5. doi: 10.11648/j.ajtte.20170201.11
Copyright
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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