Digitalization of Transport Services as a Way to Improve the Environmental Situation of Large Cities
- DOI
- 10.2991/aebmr.k.200114.069How to use a DOI?
- Keywords
- transport service, digitalization, detector, intelligent system, ecology
- Abstract
The Relevance of the study is due to the fact that the orderly movement of traffic flows, reducing downtime and congestion, due to the digitalization of transport services, will ensure their implementation on time and reduce the burden on the environment. The aim of the study is to develop an empirical model that links the results of flow detection and their evaluation by satellite intelligent systems to optimize motion. The research methods were analysis, comparison, identification of contradictions, synthesis based on the study of scientific information; observation of practical implementation of detection and optimization of transport flows; modeling of prospects for digitalization of this sphere. The novelty of this study is the theoretical justification of the possibilities of digitalization of transport services for dynamic traffic management, while improving the environmental situation in large cities. The proposed empirical model of digitalization of transport services sphere has practical value. it provides the possibility of integration of data from motion detectors and intelligent systems with subsequent modeling of flows and issuance of corrective actions.
- Copyright
- © 2020, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - E.V. Bardasova AU - E.I. Utkina PY - 2020 DA - 2020/01/18 TI - Digitalization of Transport Services as a Way to Improve the Environmental Situation of Large Cities BT - Proceedings of the First International Volga Region Conference on Economics, Humanities and Sports (FICEHS 2019) PB - Atlantis Press SP - 295 EP - 298 SN - 2352-5428 UR - https://doi.org/10.2991/aebmr.k.200114.069 DO - 10.2991/aebmr.k.200114.069 ID - Bardasova2020 ER -