Cloud computing will be key to meeting many of the challenges to store and access the huge volume of big transportation data.
Challenges and opportunities for handling the volume, velocity, and variety of transportation data and harnessing for decision-making purposes.
Made Public Date


United States

A Perspective on the Challenges and Opportunities for Privacy-Aware Big Transportation Data


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. These challenges concern the volume, variety, velocity (data processing), and cybersecurity. This paper aims to provide awareness of these large-scale challenges and provides insight into how these challenges may be met.

Lessons Learned

  • Cloud computing will be key to cope with increased volumes, velocity, and variety of data. Agencies, however, may have to give up the ability to store data internally and will need to be convinced that collected data is stored sufficiently safely.
  • The sheer volume of big transportation data will likely necessitate horizontally scaled systems deployed using distributed architectural approaches. Ever-larger quantities of data will continue to place pressure on traditional vertically based Database Management Systems.
  • Agencies will likely need to increasingly devote resources to Stream Processing methods. Organizations will need to process data coming in at different rates and in real-time, which traditional batch-processing may be unable to perform.
  • Flexible, non-relational database systems may be needed to cope with a variety of data formats. Traditional structured relational database management systems that require defined data schemas may be incapable of handling and integrating data from different sources
System Engineering Elements