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Управление тарифами Ð¿Ð»Ð°Ñ‚Ð½Ñ‹Ñ Ð°Ð²Ñ‚Ð¾Ð¼Ð¾Ð±Ð¸Ð»ÑŒÐ½Ñ‹Ñ ÑÑ‚Ð¾ÑÐ½Ð¾Ðº

выпускная квалификационная работа магистра

Управление тарифами Ð¿Ð»Ð°Ñ‚Ð½Ñ‹Ñ Ð°Ð²Ñ‚Ð¾Ð¼Ð¾Ð±Ð¸Ð»ÑŒÐ½Ñ‹Ñ ÑÑ‚Ð¾ÑÐ½Ð¾Ðº

Abstract

Данная выпускная квалификационная работа посвящена вопросам ценообразования на парковку в центральном районе Санкт-Петербурга, где есть платная стоянка. Основной категорией транспортных средств, пользующихся парковкой не только в центре, но и за городом, являются транспортные средства категории В или легковые автомобили. Анализ автомобильной промышленности в мире и в России соответствует тому, что автомобильная промышленность постоянно растет, и параллельно с этим увеличивается потребность в парковочных местах в транспортной системе каждого города. В работе анализируется проблема парковочных мест и политика ценообразования, затрагивающая всю транспортную систему Санкт-Петербурга. Охватываемая территория разделена на двенадцать зон, и каждая из них имеет свои правила использования пространства. Проанализированы международные и отечественные правила и инновационные методы оптимизации модели ценообразования на парковке. Учитывая, что система парковки состоит из различных типов камер и датчиков, данные были собраны за период с 01.12.2022 по 19.12.2022 и, зная правила и методы ценообразования на парковке, был проведен полный анализ данных для выяснения текущего состояния системы. система парковки, которая имеет множество показателей эффективности. В соответствии с проведенным анализом и путем моделирования различных правил и ситуаций даются рекомендации в зависимости от того, какие показатели необходимо максимизировать.

This final qualification work is devoted to the issues of parking pricing in the central area of Saint Petersburg where there is paid parking. Main category of vehicles that are using parking not only in the center but even outside the city are category B vehicles or cars. Analyzes of the automobile industry worldwide and in Russia is corresponding, the automotive industry is constantly rising and parallel to that the need for parking space is increasing its effect in the transport system of every city. The work analyzes the problem with parking space and the politic of pricing which affect the whole transport system of Saint Petersburg. The area covered is divided into twelve zones and each one of them has its own rules for space usage. International and domestic rules and innovative methods for optimizing the parking pricing model were analyzed. Given that the parking system consists of different types of cameras and sensors, data was collected from 01.12.2022 till 19.12.2022 and knowing the rules and methods for parking pricing complete data analyzes were made to find out the current state of the parking system which has a lot of efficiency indicators. In according to the analysis carried out and by simulating different rules and situations, recommendations are given depending on which indicators needs to be maximized.

Keywords

корреляция, autocad, price elasticity, excell modeling, corelation, policy scenarios, parking pricing, transport planning, эластичность цены, моделирование excell, планирование транспорта, ценообразование парковки

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
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