Big Data vs Congestion


1) Sustainability problem: Mobility

  • Traffic and congestion on the road, by sea, in the air, on the rails—wasted productivity, increases pollution (air quality and GHGs) and is costly to society.

2) Summary:

  • Utilizing existing infrastructure through improved demand management and deployed maintenance.
  • Through digitization (big data), the collection and strategic use of information to forecast.
  • Influence behavior in to improve the reliability and efficiency of transport infrastructure.
  • Use pattern recognition, re-allocation of assets and dynamic pricing to effect travel.

3) Stakeholders:

  • Local government/municipalities
  • Commuters
  • Freight carriers
  • Infrastructure construction entities

4) Deployment:

  • Identity the data streams and integrate the logic of the travel modes and various system goals.
  • Establish transparency of the data and computer systems.
  • Understand the share of costs and benefits to various stakeholders to properly manage.
  • Engage the regulatory entities to encourage cooperation.

Article: Big Data vs Traffic


One thought on “Big Data vs Congestion

  1. It was interesting to read about a specific application. In Israel, the system can count the cars on the road, and by evaluating the space between the cars, it can measure congestion. Tolls are based on traffic at the time of travel. That is, if traffic density is high, tolls are high; if there are few cars on the road, charges are cheap. In this way, they maximize toll revenue and work to reduce congestion by “steering” demand.


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