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

• Published in: International journal of production economics 2021-01, Vol.231, p.107868, Article 107868
• Main Authors: Kaffash, Sepideh, Nguyen, An Truong, Zhu, Joe
• Format: Article
• Language: English
• Subjects: Big data algorithms; Intelligent transportation system; Survey; Traffic flow prediction
• ISSN: 0925-5273; 1873-7579
• DOI: 10.1016/j.ijpe.2020.107868

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. •We review the most relevant big data algorithms used in intelligent transportation systems.•We review the most relevant applications of ITS covered by big data algorithms.•We provide a comprehensive bibliography review of 586 papers in the field.•We generate a framework connecting the recognized big data algorithms to various ITS applications.