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Mobile crowdsourcing platform for intelligent car park systems

机译:智能停车场系统的移动众包平台

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Mobile crowdsourcing concept has attracted attentions of researchers, developers and businesses in the last decade. This exact concept has also been used in the area of Intelligent Transportation System (ITS) mainly for collecting and distributing information about the current traffic condition. In this paper, we extend the mobile crowdsourcing concept to be used for an intelligent car park system. Among several existing applications, the system proposed in this paper has been designed so that it is suitable for the car parking behavior exhibited in asian countries. To be specific, the Pick N Park system was proposed and implemented to gather and deliver real-time information about a number of car parks in crowded urban areas. The proposed system not only assists drivers in planning their journeys; but it also helps alleviate the traffic congestion problem especially in front of the shopping malls (where a line of cars waiting to enter the car park blocks other traffic). In addition to the system, we also propose a car park model that can be used to estimate the congestion level and the search time of each car park. This can be useful especially during the initial phase that the technology is introduced. The model has been evaluated by monte-carlo simulations and the results show that the proposed model can provide excellent search time estimates.
机译:移动众群概念在过去十年中引起了研究人员,开发商和企业的关注。这种确切的概念也已在智能交通系统(其)领域用于收集和分发有关当前流量条件的信息。在本文中,我们扩展了移动众包概念,用于智能停车场系统。在若干现有申请中,本文提出的系统已经设计成使其适用于亚洲国家的停车行为。具体而言,提出并实施了Pick N Park系统,以收集有关拥挤城市地区的许多停车场的实时信息。拟议的系统不仅有助于驾驶员计划他们的旅程;但它还有助于减轻交通拥堵问题,特别是在购物中心面前(在那里等待进入停车场块的车辆区块其他流量)。除了系统之外,我们还提出了一个停车场模型,可用于估计每个停车场的拥堵水平和搜索时间。这可以特别是在介绍技术的初始阶段。该模型已由Monte-Carlo仿真评估,结果表明,所提出的模型可以提供出色的搜索时间估计。

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