A Review of Big Data in Road Freight Transport Modeling–Gaps and Potentials

Wasim Shoman, Sonia Yeh, Francis Sprei, Jonathan Köhler, Patrick Plötz, Yancho Todorov, Seppo Rantala, Daniel Speth

Research output: Contribution to journalArticleScientificpeer-review


Recent developments in 'Big Data' can provide useful information such as individual behaviors and activities in addition to aggregated patterns using conventional datasets. This paper summarizes state of the art in analyzing Big Data sources concerning road freight transport (RFT) and the current knowledge gaps by identifying key challenges and promising areas for future opportunities. Various challenges hinder access and utilization of Big Data for RFT applications , including organizational, privacy, technical expertise, and legal challenges. We note that the environment for sharing data for research is still in its infancy. Improving access and use of Big Data will require political support to ensure all involved parties that their data will be safe and contribute positively toward a common goal, such as a more sustainable economy. We identify the areas for further research, including data collection, data analytics, and applications to support decision-making categories.
Original languageEnglish
Number of pages33
JournalTransportation Research Part D: Transport and Environment
Publication statusE-pub ahead of print - 13 Jul 2022
MoE publication typeA1 Journal article-refereed


  • big data
  • big data analytics
  • road freight transport
  • transport modeling


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