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A Decision Support System for Reducing CO2 and Black Carbon Emissions by Adaptive Traffic Management

The CARBOTRAF project aims to realize a method, system and tools for adaptively influencing traffic in real-time to reduce carbon dioxide CO2 and black carbon (BC) emissions caused by road transport in urban and inter-urban areas. The inter-relationships between traffic states and CO2 and BC emissions are investigated. In particular a model linking traffic states to emission levels was established on the basis of existing and new (traffic) simulation methods and tools. A KPI-based decision support system for online prediction of emission levels uses real-time and simulated traffic and air-quality data. Based on this prediction a low emission traffic scenario is achieved by imposing ITS measures (re-routing, adjustment of traffic light sequences).

Services provided by CARBOTRAF:

  • Analyzing the most relevant user needs and requirements for achieving the CO2 reduction via Stakeholder interviews and workshops
  • Definition of a set of traffic and emission related KPIs
  • Development and semi-automated calibration of a microscopic transport model (VISSIM) of the test site in Graz
  • Microscopic traffic simulation of various scenarios
  • Emission calculation (AIRE)
  • Scenario assessment by means of defined KPIs


The CARBOTRAF project was funded by the European Commission / FP7 (FP7-ICT-2011-7) under grant agreement no. 287867.