Abstract
A constant problem in big cities is the necessity to develop and enhance urban transit systems at a good pace. The main task is to improve the comfort of passengers using public transport. There are a number of indicators by which to value the convenience of the transport system of the metropolis. To compute these indicators, we analyzed the data obtained from the municipal information systems: the public transport payment system and transport tracking system. We evaluated the following indicators: rush hours during the day, average amount of trips made by passengers of each group per month, transportation comfort index, most and least comfortable districts of the city, interchange coefficient for regular trips and ordinary multimodal trips (average number of single trips within multimodal trip), average regular trip time consumption etc.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Grafeeva, N., Mikhailova, E., Nogova, E., Tretyakov, I.: Passenger traffic analysis based on St. Petersburg public transport. In: 17th International Multidisciplinary Scientific GeoConference: Informatics, Geoinformatics and Remote Sensing, SGEM 2017, Albena, Bulgaria, vol. 17, no. 21, pp. 509–516 (2017)
Yaping, R., Xingchen, Z., Baiyun, Lu, L., Yao, C., Yiwei, S.: Life cycle cost analysis of urban rail transit vehicle. IEEE (2015)
He, S., Gan, H., Xu, F.: Analysis of resilience for urban transit networks. IEEE (2011)
Ma, C., Wang, Y., Guo, Y.: Sensitivity analysis on urban rail transit passenger flow forecast. IEEE (2011)
Zhang, J., Fan, Y.-H., Nai, W., Yu, Y.: Analysis on impact factors of travel speed and their countermeasures for Shanghai urban rail transit network. IEEE (2015)
Sun, Y., Pan B.: A comparative analysis of the scope of influence of urban rail transit on the values of real estate in different surrounding regions. IEEE (2011)
Lessard, R.: The use of computer for urban transit operations. IEEE (1993)
Fedorov, V.P., Losin, L.A.: Mathematical modeling methods for urban transit system projecting on pre-network level. Russian Federation Transport, № 2, p. 39 (2012)
Zhang, G., Zhang, H., Li, L., Dai, C.: Agent-based simulation and optimization of urban transit system. IEEE (2013)
Shvecov, V.I.: Movement in transit system modeling problems. Moscow Federal Technician Institute Works, vol. 2, № 4 (2010)
Acknowledgments
Topics for research were chosen using assistance of Saint Petersburg transportation system institute. Computational results were obtained using equipment of Computing Centre of Saint Petersburg State University Research Park.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Grafeeva, N., Tretyakov, I., Mikhailova, E. (2018). Quality Analysis of Urban Transit System in St. Petersburg. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S. (eds) Trends and Advances in Information Systems and Technologies. WorldCIST'18 2018. Advances in Intelligent Systems and Computing, vol 746. Springer, Cham. https://doi.org/10.1007/978-3-319-77712-2_84
Download citation
DOI: https://doi.org/10.1007/978-3-319-77712-2_84
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-77711-5
Online ISBN: 978-3-319-77712-2
eBook Packages: EngineeringEngineering (R0)