Good Data, the Business Model Conundrum, and ITS Policy

Intelligent Transportation Systems (ITS) provide reliable, timely, and quality data delivered in real time. Originally designed primarily for operators of the transportation system or as a snapshot of travel conditions, ITS data is increasingly collected and processed by private entities, often using new, more cost effective technologies. This paper explores this trend, focusing on data quality, business models, and policy development in ITS. The author cautions that with this transition come several critical policy issues that relate not only to the data, but also the access to this data, and the ability to use the data more broadly to make the transport system more efficient and thereby the economy more productive. The author outlines a concept that may solve the business model conundrum. The conundrum arises from the need to simultaneously provide the means to get good data, cover all the associated costs, and share the data, data which will be used to increase the efficiency of individual, commercial, and operational decisions. The concept frames the ITS data as a public good and the shared data pool would be populated by data from a wide range of stakeholders in both public and private sectors. Supply and demand for the data would create a market value for the data in the pool over time.


  • English

Media Info

  • Media Type: CD-ROM
  • Features: References;
  • Pagination: 5p
  • Monograph Title: ITS Connections: Saving Time. Saving Lives

Subject/Index Terms

Filing Info

  • Accession Number: 01142488
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Oct 12 2009 11:26AM