Traffic Emission Prediction scheme (TEPs)

Traffic Emission Prediction scheme (TEPs)Traffic Emission Prediction scheme (TEPs)Traffic Emission Prediction scheme (TEPs)

Traffic Emission Prediction scheme (TEPs)

Traffic Emission Prediction scheme (TEPs)Traffic Emission Prediction scheme (TEPs)Traffic Emission Prediction scheme (TEPs)
  • Home
  • Features
    • TEPs-I: Traffic module
    • TEPs-II: emission module
    • Satellite data for TEPs
  • Applications
    • PECOUNT-I
    • PECOUNT-II
    • PRTCS
    • KCOUNT
    • OptimStation
  • Results
    • Case Studies
  • Publications
  • TEPs in other websites
  • More
    • Home
    • Features
      • TEPs-I: Traffic module
      • TEPs-II: emission module
      • Satellite data for TEPs
    • Applications
      • PECOUNT-I
      • PECOUNT-II
      • PRTCS
      • KCOUNT
      • OptimStation
    • Results
      • Case Studies
    • Publications
    • TEPs in other websites

  • Home
  • Features
    • TEPs-I: Traffic module
    • TEPs-II: emission module
    • Satellite data for TEPs
  • Applications
    • PECOUNT-I
    • PECOUNT-II
    • PRTCS
    • KCOUNT
    • OptimStation
  • Results
    • Case Studies
  • Publications
  • TEPs in other websites

OptimStation

Overall structure

 OptimStation is an optimization routine that was developed to find optimal locations for new traffic count stations.


The main idea is finding locations in a city that minimize error in estimated Annual Average Daily Traffic. This model suggests taking advantage of KCOUNT routine and Genetic Algorithms to improve the design of a traffic network. The optimization problem consists in minimizing an objective function defined here as the average prediction error over all roads with monitored traffic counts.  

  

 This project was supported by The City of Toronto's Transportation Services Division  and Atmospheric Fund

 

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Updated on Feb 28, 2019