Gravity Modelling of Car Sharing Based on PTV Visum
https://doi.org/10.30932/1992-3252-2019-17-222-241
Abstract
Car sharing plays an important role in the transition to unmanned vehicles. This article discusses the positive and negative aspects of the existing car sharing system in Russia, as well as forecast trends using the examples of Moscow and St. Petersburg. Since car sharing in St. Petersburg is not yet sufficiently developed, and the forecasts of operators on the market capacity diverge, it is of interest to determine the conditions facilitating successful development of the service, and to evaluate the city’s need for the number of cars used by car sharing services.
The objective of the research described in the article is to study the trends in development of car sharing services, to determine the estimates of the required number of cars for car sharing services, and intensity of their rental in a particular city district. To solve the problem, the gravity modelling method is used based on the PTV Visum 18 software. Whilst special tools of the developed line of PTV MaaS programs (Controller, Operator, Simulator, Modeller) are not applied, it allows to build transport models of the macro level and perform transport modelling taking into account new forms of mobility (car sharing, bike sharing, etc.) while planning and management of urban transport systems.
The solution to the problem in volved development of two models of transport demand for the selected district of the city: considering and without considering car sharing effect. In the process of modelling, we studied the structure of transport time expenditures following changes in the number of vehicles in the fleet and intensity of its rental regarding several operator tariffs. The critical number of cars used by car sharing services for the city district was determined under the conditions of the greatest competition of these cars with individual vehicles. It is shown that under current conditions, the effect of reducing timerelated transport costs in the district is about 14 % when using one-year simulation horizon. The simulation results are consistent with the real data on trips and can be extrapolated to other city districts.
The objective of the research described in the article is to study the trends in development of car sharing services, to determine the estimates of the required number of cars for car sharing services, and intensity of their rental in a particular city district. To solve the problem, the gravity modelling method is used based on the PTV Visum 18 software. Whilst special tools of the developed line of PTV MaaS programs (Controller, Operator, Simulator, Modeller) are not applied, it allows to build transport models of the macro level and perform transport modelling taking into account new forms of mobility (car sharing, bike sharing, etc.) while planning and management of urban transport systems.
The solution to the problem in volved development of two models of transport demand for the selected district of the city: considering and without considering car sharing effect. In the process of modelling, we studied the structure of transport time expenditures following changes in the number of vehicles in the fleet and intensity of its rental regarding several operator tariffs. The critical number of cars used by car sharing services for the city district was determined under the conditions of the greatest competition of these cars with individual vehicles. It is shown that under current conditions, the effect of reducing timerelated transport costs in the district is about 14 % when using one-year simulation horizon. The simulation results are consistent with the real data on trips and can be extrapolated to other city districts.
About the Author
S. A. Andronov
St. Petersburg State University of Aerospace Instrumentation (SUAI)
Russian Federation
Russian Federation
Ph.D. (Eng), Associate Professor of the Department of System Analysis and Logistics
St. Petersburg
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For citations:
Andronov S.A. Gravity Modelling of Car Sharing Based on PTV Visum. World of Transport and Transportation. 2019;17(6):222-241. https://doi.org/10.30932/1992-3252-2019-17-222-241
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