Emission and Traffic Efficiency


This module addresses mechanisms and strategies to improve traffic efficiency and carbon footprint. The objectives are first to introduce the underlying theory such as Waldrop Equilibrium required for efficient path planning. Second, it describes concepts and theory behind the optimization of traffic lights to traffic conditions. Third, it provides guidelines and methodologies to model emissions and integrate them into efficient path planning.  Finally, it trains on best practices to apply these concepts for efficient and green path planning on vehicular traffic simulators.

Teaching and Learning Methods: Lectures and Lab sessions (group of 2 students)

Course Policies: Attendance to Lab sessions is mandatory.


  • Basic graph theory knowledge
  • Basic C++ and Bash / Python knowledge


Graph Theory

  • Shortest Path Planning
  • Travelling Salesman

Dynamic Traffic Equilibrium

  • Waldrop Equilibria
  • Dynamic Demand Assignment

Traffic Light Control

  • Static traffic light controller
  • Actuated & Dynamic traffic light controllers

Emission and Air Quality

  • Pollutant classes (CO, CO2, NOx,...)
  • HandBook on Emission Factors for Road Traffic  (HBEFA)

Advanced Topics

  • Self-Organizing Traffic Light Controller
  • Green Light Speed Advisory
  • Floating Car Data

Learning outcome: 

  • To be able to understand dynamic equilibria for vehicular path planning
  • To be able to model efficient traffic light controllers
  • To be able to analyze the impact of traffic on emissions and pollutants
  • To be able to apply these concepts for efficient and green scenario design on traffic simulators
  • Basic C++ and Bash / Python knowledge

Nb hours: 21.00


  • Lab reports (50% of the final grade),
  • Final Exam (50% of the final grade)