Извините, этот техт доступен только в “Американский Английский”. For the sake of viewer convenience, the content is shown below in the alternative language. You may click the link to switch the active language.
A MATHEMATICAL MODEL OF DEMAND MANAGEMENT FOR CARSHARING
Mark E. Koryagin, professor of the department of «Higher Mathematics», Siberian Transport University, Novosibirsk, Russia, markkoryagin@yandex.ru
Vladislav S. Izvekov, Lecturer of the department of «Higher Mathematics», Siberian Transport University, Novosibirsk, Russia, vlad-izvekov@mail.ru
Vladimir N. Katargin, professor, Candidate of Technical Sciences, Siberian Federal University, Krasnoyarsk, Russia, vkatargin@sfu-kras.ru
Abstract
A significant increase of carsharing service in Russia and worldwide has led to need a formal description of the process orders fulfilling on the service. The paper presents a mathematical model for computation the distance between customers and free car, which is built on the basis of the «nearest neighbor»method. A model of demand generation is proposed. The demand depends on the potential number of customers and the probability of finding a car in the area of walking distance. The number of free cars is described as stochastic process, which is based on a birth and death process. The death intensity in the process depends on the probability of finding a car. The estimation of the average number of free cars, their average load and the probability of finding a free car in the walking distance are obtained. The combination of the presented models allows to assess the impact of the number of carsharing vehicles on demand. In particular, a numerical example shows that an increase in the carsheribg fleet can lead to increaseasing in the cars average load. Thus, we can conclude that a larger car-sharing project can be cost-effective only if the carsharing service consists of a large fleet of vehicles, i.e. the service contains a high density of free cars.
Keywords: carsharing, the nearest neighbor method, pbirth and death process, travel demand management. urban transport system.
References
1. V. Vuchik (2017). Transport in cities convenient for life. Litres. 820 p.
2. I.S. Zyryanova (2018). Car rental as a service industry: geographical and organizational aspects. Regional studies. No. 1. P. 156-165.
3. N.S. Bagrov, D.V. Denisov (2019). The problem of dynamic redistribution of cars of the car-sharing service. International Journal of Open Information Technologies. 2019. Vol. 7. No. 8. P. 14-25.
4. M. P. Malinovsky, T. K. Arakelyan (2018). Carsharing: problems of participants and outsiders. Automobile. Road. Infrastructure. = Avtomobil ‘. Doroga. Infrastruktura. No. 3 (17). 13 p.
5. Chen, Tong Donna (2015). Management of a shared, autonomous, electric vehicle fleet: vehicle choice, charging infrastructure & pricing strategies. PhD dissertation. University of Texas at Austin. 2015. 120 p.
6. B. Boyac, K. G. Zografos, N. Geroliminis (2015). An optimization framework for the development of efficient one-way car-sharing systems. European Journal of Operational Research. 2015. Vol. 240. No. 3. P. 718-733.
7. S.P. Kharitonov (2005). The «nearest neighbor» method for the mathematical assessment of the distribution of biological objects on the plane and on the line. Bulletin of the Nizhny Novgorod University. NI Lobachevsky. Series: Biology. No. 1. P. 213-221.
8. P. J. Clark, F. C. Evans (1954). Distance to nearest neighbor as a measure of spatial relationships in populations. Ecology. Vol. 35. No. 4. P. 445-453.
9. M.A. Berfeld (2020). Forecasting the number of cars in urban agglomeration in the context of modernization of the transport system and socio-economic conditions: Mag. dis. 23.04.03.68.01 «Operation of transport and technological machines and complexes» Siberian Federal University, 86 p. http://elib.sfu-kras.ru/bitstream/handle/2311/136812/berfeld_na_sayt.pdf?sequence=1
10. R. Sidorchuk et al. Modeling of the need for parking space in the districts of Moscow metropolis by using multivariate methods. Journal of Applied Engineering Science. 2020. Vol. 18. No. 1. P. 26-39.
11. F. E. Prettenthaler, K. W. Steininger (1999). From ownership to service use lifestyle: the potential of car sharing. Ecological economics. Vol. 28. No. 3. P. 443-453.
12. D. Jorge, G. H. A. Correia, C. Barnhart (2014). Comparing optimal relocation operations with simulated relocation policies in one-way carsharing systems. IEEE Transactions on Intelligent Transportation Systems. Vol. 15. No. 4. P. 1667-1675.
13. D. Jorge, C. Barnhart, G. H. de Almeida Correia (2015). Assessing the viability of enabling a round-trip carsharing system to accept one-way trips: Application to Logan Airport in Boston. Transportation Research Part C: Emerging Technologies. Vol. 56 . P. 359-372.
14. T. Litman (2000). Evaluating carsharing benefits. Transportation Research Record. Vol. 1702. No. 1. P. 31-35.
15. M.A. Berfeld (2020), Mathematical modeling of the probability of having a car sharing within walking distance / MA Berfeld, ME Koryagin, VN Katargin. Modern technologies. System analysis. Modeling. No. 3 (67). P. 54-59. DOI 10.26731 / 1813-9108.2020.3 (67) .54-59.
16. TDM Encyclopedia [electronic resource]: Why Manage Transportation Demand? URL: https://www.vtpi.org/tdm/tdm51.htm (date of the application: 29.04.2021)
17. The Federal Highway Administration’s [electronic resource]: Travel Demand Management URL: http://ops.fhwa.dot.gov/aboutus/one_pagers/demand_mgmt.htm (date of the application: 29.04.2021)
18. Social Impact Open Repository [electronic resource]: URL: http://sior.ub.edu/jspui/cris/socialimpact/socialimpact00441 (date of the application: 29.04.2021)
19. Michael G. McNally// The four-stage model. In: A Handbook on Transport Modeling, ed. David A. Hensher and Kenneth J. Button, Elsevier, 2000. P. 35-52.
Information about authors:
Mark E. Koryagin, professor of the department of «Higher Mathematics», Siberian Transport University, Novosibirsk, Russia
Vladislav S. Izvekov, Lecturer of the department of «Higher Mathematics», Siberian Transport University, Novosibirsk, Russia
Vladimir N. Katargin, professor, Candidate of Technical Sciences, Siberian Federal University, Krasnoyarsk, Russia