2018/11/23 by Godwin Badu-Marfo, Bilal Farooq, Zachary Patterson · 24 citations
Computer Science · Engineering · Social Sciences · #Big data #Human Mobility and Location-Based Analysis #Information system #Intelligent transportation system #Perspective (graphical) #Privacy-Preserving Technologies in Data #Scale (ratio) #Traffic Prediction and Management Techniques #Transportation industry #Transportation planning #cs.CY
paper · pdf · doi:10.1007/s42421-019-00001-z
published in Journal of Big Data Analytics in Transportation 1(1), 1-23 (Springer Science+Business Media) · Accepted for publication in the Journal of Big Data Analytics in Transportation
arxiv created 2018/11/23 · openalex created_date 2018/11/29 · arxiv updated 2019/03/21 · openalex publication_date 2019/04/04 · openalex updated_date 2026/08/05
In recent years, and especially since the development of the smartphone, enormous amounts of data relevant for transportation have become available. These data hold out the potential to redefine how transportation system (i.e. design, planning and operations) is done. While researchers in both academia and industry are making advances in using this data to transportation system ends (e.g. information inference from collected data), little attention has been paid to four larger scale challenges that will need to be overcome if the potential for Big Transportation Data is to be harnessed for transportation decision-making purposes. This paper aims to provide awareness of these large-scale challenges and provides insight into how we believe these challenges are likely to be met.