Abstract 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.

中文翻译：

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大数据算法及在智能交通系统中的应用：综述与文献计量分析

摘要 智能交通系统 (ITS) 中数据的数量和可用性导致需要数据驱动的方法。应用大数据算法，进一步提升交通领域应用的智能化。应用大数据算法越来越受到ITS学术和工业领域的关注。智能交通系统中的大数据算法具有广泛的应用，包括但不限于信号识别、物体检测、交通流预测、出行时间规划、出行路线规划以及车辆和道路的安全。该调查旨在提供参考书目、对 ITS 应用的全面审查以及对在 ITS 背景下使用的大数据的最公认模型的审查。1997-2019 年期间审查了 586 篇论文。本研究深入洞察了大数据算法在 ITS 中的应用，揭示了这些应用的不同领域，并整合了模型和应用。研究结果确定了未来的研究差距和方向。