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首页> 外文期刊>International journal on Semantic Web and information systems >An Adaptive and Hotspot Aware Taxi Zone Queuing System on Internet of Vehicles
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An Adaptive and Hotspot Aware Taxi Zone Queuing System on Internet of Vehicles

机译:车辆互联网上的自适应和热点意识到出租车区排队系统

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摘要

>Taxis have a vital role in the transportation system and Internet of Vehicles (IoV) techniques can be used to improve the fuel and time efficiencies of taxis. However, the existing work does not address the traffic congestion that may occur when a large amount of taxis gathers in certain queuing areas. This paper proposes an adaptive and hotspot-aware taxi zone queuing system to deal with the problem while still guarantees the fuel and time efficiencies. The adaptive scheme features data collection, hotspot extraction, an adaptive zone queuing protocol, and navigation services for taxi drivers. Real data were collected from Taiwan Taxi Inc., the largest taxi company in Taiwan. Queuing zone hotspots were identified through the analysis of the collected data. The hotspots represented. A navigation service was based on the proposed protocol. To verify the feasibility of the proposed system, a prototype was implemented. The experimental results demonstrated that the proposed scheme outperformed other schemes in reducing waiting time and the average number of taxis.
机译:>出租车在运输系统中具有重要作用,并且车辆互联网(IOV)技术可用于改善出租车的燃料和时间效率。但是,现有工作没有解决可能发生在某些排队区域的大量出租车时可能发生的交通拥堵。本文提出了一种自适应和热点感知的出租车区排队系统,以处理问题,同时仍然保证燃料和时间效率。自适应方案具有数据收集,热点提取,自适应区域排队协议和出租车驱动程序的导航服务。来自台湾最大的出租车公司台湾纳税公司的实际数据。通过分析所收集的数据来确定排队区热点。热点表示。导航服务基于所提出的协议。为了验证所提出的系统的可行性,实施了原型。实验结果表明,该方案在减少等待时间和平均出租车的平均数方面表现出其他方案。

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