Volume 2, Issue 4, December 2017, Page: 96-101
Influence of the Seasonal Factor on the Long-Distance Passenger Correspondence
Dolia Kostiantyn, Department of GIS, Land and Real Estate Appraisal, O. M. Beketov National University of Urban Economy in Kharkiv, Kharkiv, Ukraine
Received: Oct. 9, 2017;       Accepted: Oct. 23, 2017;       Published: Dec. 12, 2017
DOI: 10.11648/j.ajdmkd.20170204.11      View  953      Downloads  51
Abstract
The process of transportation of passengers on inter-regional routes of general use is investigated in the article. It is established that long-distance passenger transport correspondences have fluctuations that are observed in time. Such variations can be attributed to changes in the volumes or directions of passenger transportation during the day, which are described by many researchers. In addition to the above, it is known that in the system of intercity passenger transport it is possible to observe the existence of processes for the formation of predicted changes when considering the period of transportation during the week. In this case, there is a corresponding change in the characteristics of volumes and directions of passenger correspondence on the days of the week. Similar fluctuations also occur in the consideration of the state of correspondence during the year. Intercity passenger transport systems have as their objective the functioning of a qualitative transport system and safe satisfaction of the needs for the movement of people. The presence of a stable route network scheme can be considered one of the requirements to the quality of passenger service. This leads to the need to take into account the influence of the environment of the functioning of the system in the organization of its functioning, subject to the restrictions.
Keywords
Transport System, Gravity Model, Seasonal Fluctuations of Transport Correspondences, Long-Distance Transportation
To cite this article
Dolia Kostiantyn, Influence of the Seasonal Factor on the Long-Distance Passenger Correspondence, American Journal of Data Mining and Knowledge Discovery. Vol. 2, No. 4, 2017, pp. 96-101. doi: 10.11648/j.ajdmkd.20170204.11
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.
Reference
[1]
Andronov, A., & Santalova, D. (2009). On Nonlinear Regression Model for Correspondence Matrix of Transport Network. In Selected papers of the International Conference Applied Stochastic Models and Data Analysis (pp. 90-94).
[2]
Baik, H., Trani, A., Hinze, N., Swingle, H., Ashiabor, S., & Seshadri, A. (2008). Forecasting model for air taxi, commercial airline, and automobile demand in the United States. Transportation Research Record: Journal of the Transportation Research Board, (2052), 9-20.
[3]
Seedat, I. (1973). Implementing the 2007 Public Transport Strategy and Action Plan: transportation. Civil Engineering= Siviele Ingenieurswese, 15 (9), 13-16.
[4]
Terekhov, I., Ghosh, R., & Gollnick, V. (2015). A concept of forecasting origin-destination air passenger demand between global city pairs using future socio-economic scenarios. In 53rd AIAA Aerospace Sciences Meeting.
[5]
Khan, A. M. (1981). II. Intercity passenger transportation: energy efficiency and conservation case study. Transportation Planning and Technology, 7 (1), 1-9.
[6]
Dolya, C. Modeling of passenger transport correspondence between regional centers in Ukraine [Text] / C. Dolya // Journal of Technology audit and production reserves. – 2017. – V. 1, No. 2 (33). – P. 44-48.
[7]
Grigorova, T., Davidich, Y., & Dolya, V. (2015). Transport Fatigue Simulation of Passengers in Suburban Service. International Journal of Automation, Control and Intelligent Systems, 1 (2), 87-99.
[8]
Dolya, C. (2017). Modeling of intercity passenger transportation system. Technology audit and production reserves, (2 (2)), 37-43.
[9]
Grigorova T., DavIdIch Yu., Dolya V. (2015). Assessment of elasticity of demand for services of suburban road passenger transport. Technology audit and production reserves. 3. 2 (23). 13–16.
[10]
Yves Crozet (2009), he prospects for inter-urban travel demand. Future for interurban passenger transport: bringing citizens closer together: 18th International Symposium on Transport Economics and Policy, 16-18 November 2009, Madrid.
[11]
Nokandeh, M. M., Ghosh, I., & Chandra, S. (2015). Determination of Passenger-Car Units on Two-Lane Intercity Highways under Heterogeneous Traffic Conditions. Journal of Transportation Engineering, 142 (2), 04015040.
[12]
Schwieterman, J. P., Antolin, B., Levin, A., & Michel, M. (2016). The Remaking of the Motor Coach: 2015 Year in Review of Intercity Bus Service in the United States. Chicago, IL: Chaddick Institute for Metropolitan Development, DePaul University.
[13]
Borndörfer, R., Reuther, M., Schlechte, T., Waas, K., & Weider, S. (2015). Integrated optimization of rolling stock rotations for intercity railways. Transportation Science, 50 (3), 863-877.
[14]
Li, T. (2016). A Demand Estimator Based on a Nested Logit Model. Transportation Science.
Browse journals by subject