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Big data algorithms and applications in intelligent transportation system: A review and bibliometric analysis

机译:智能交通系统的大数据算法和应用:综述与讲学计量分析

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摘要

The volume and availability of data in the Intelligent Transportation System (ITS) result in the need for data driven approaches. Big Data algorithms are applied to further enhance the intelligence of the applications in the transportation field. Applying Big Data algorithms has increasingly received attention in both the academic and industrial fields of ITS. Big Data algorithms in ITS have a wide range of applications including but not limited to signal recognition, object detection, traffic flow prediction, travel time planning, travel route planning and safety of vehicle and road. This survey aims to provide a bibliography, a comprehensive review of the application of ITS and a review of most recognized models with Big Data used in the context of ITS. 586 papers are reviewed over the period 1997-2019. This study provides a deep insight into applications of Big Data algorithms in ITS, revealing different areas of those applications and integrates models and applications. The result of the study identifies research gaps and direction for the future.
机译:智能交通系统中数据的卷和可用性(其)导致需要数据驱动的方法。应用大数据算法以进一步增强运输场中应用的智能。应用大数据算法在其学术和工业领域越来越受到关注。其具有广泛的应用程序中的大数据算法,包括但不限于信号识别,对象检测,交通流量预测,旅行时间规划,车辆和道路的行程规划和安全。该调查旨在提供书目,全面审查其应用程序的应用以及对大多数公认模型的审查,其中包含在其背景下使用的大数据。 1997 - 2019年期间审查了586篇论文。本研究提供了深入了解大数据算法的应用,揭示这些应用的不同区域并集成了模型和应用程序。该研究的结果识别了未来的研究差距和方向。

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