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Development of Prediction Model for Real-Time Parking Availability for On-Street Paid Parking

机译:路边收费停车场实时停车可用性预测模型的开发

摘要

This research is based on the need for a parking information system to provide on- street parking availability information in the neighborhoods in the City of Pittsburgh has been established. This project intends to provide a methodology to determine the real-time parking availability information for on street parking operators.udAs a part of this project, this research models the parking availability with no specialized hardware other than purchased parking time from a kiosk type pay system. The prediction model developed is based on the sample data collected with no real-time data required other than paid time information.udBecause paid parking systems only record the time of arrival and paid parking time, the actual departure time and thus the availability of the parking space is unknown. This research determined the relationship between over-paid on-street parking time, which means that the owner pays more than the actual parking time needs and how this relates to parking space availability for next vehicle based on actual on-street parking time. Many variables may influence over-paid parking time, such as trip purpose types of users, weather conditions and temporal distribution. All of these variables were explored to develop the predictive model.
机译:这项研究基于对停车信息系统的需求,该系统已在匹兹堡市附近提供路边停车可用性信息。该项目旨在提供一种确定路边停车操作员的实时停车可用性信息的方法。 ud作为该项目的一部分,本研究对停车可用性进行了建模,除了从售货亭类型的工资中购买的停车时间外,没有专门的硬件系统。开发的预测模型基于收集的样本数据,除了付费时间信息外,不需要任何实时数据。 ud因为付费停车系统仅记录到达时间和付费停车时间,实际出发时间以及因此的可用性停车位未知。这项研究确定了多付的路边停车时间之间的关系,这意味着车主支付的费用超过了实际停车时间的需求,并且这与基于实际路边停车时间的下一辆车的停车位可用性有何关系。许多变量可能会影响超额支付的停车时间,例如用户的出行目的类型,天气条件和时间分布。探索了所有这些变量以建立预测模型。

著录项

  • 作者

    Liu Chang;

  • 作者单位
  • 年度 2016
  • 总页数
  • 原文格式 PDF
  • 正文语种 en
  • 中图分类

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