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Analyzing External Factors on the Spatial and Temporal Demand of Car Sharing Systems

机译:分析共享汽车时空需求的外部因素

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During the last decades, Car Sharing emerged as a new important type of mobility service, different systems are installed and operated today. For an efficient and economic operation of any Car Sharing system, the identification of customer demand is essential. This demand is investigated within the presented research by analyzing booking data of two Car Sharing systems. The objective is to identify different influences on the usage of Car Sharing. Parameters to investigate are manifold: they can include those easy to measure like hourly or daily changes in usage and also influences like weather or socio-demographic data. Therefore both the spatial and the temporal points of highest or lowest demand have to be identified and linked with the given data of the different parameters. This paper describes how the interdependencies can be identified. The given data is analyzed in order to identify spatial and temporal Hot-Spots and Cold-Spots with high respectively low frequency of bookings. By overlying these results with the different parameters the existence of interdependencies can be described.
机译:在过去的几十年中,汽车共享已成为一种新型的重要出行服务,如今已安装并运行了各种系统。为了使任何汽车共享系统高效,经济地运行,识别客户需求至关重要。通过分析两个汽车共享系统的预订数据,可以在本研究中调查这种需求。目的是确定对共享汽车使用的不同影响。要研究的参数是多种多样的:它们可以包括易于测量的参数,例如每小时或每天的使用变化,以及诸如天气或社会人口统计数据的影响。因此,最高或最低需求的空间和时间点都必须被识别,并与不同参数的给定数据链接。本文介绍了如何识别相互依赖性。分析给定的数据,以识别分别具有高预定频率和低预定频率的时空热点和冷点。通过用不同的参数覆盖这些结果,可以描述相互依赖性的存在。

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