Balancing congestion and emissions in urban networks via path-based incentives

This study investigates the potential of path-based incentives to mitigate congestion and reduce emissions in urban transport networks using a multi-objective optimisation problem with a budget limit. A column generation-based solution technique is developed that finds a new path between each origin-destination pair at each iteration, and stops when the objective value does not change more than a threshold at two consecutive iterations. Three different scenarios are defined based on the objective function: minimising total travel time (TTT), total emissions (TE), and integrated minimisation of both. Numerical results in the Sioux Falls network show that TTT and TE are conflicting objectives under our modeling assumptions: improving one worsens the other. Nonetheless, the integrated scenario demonstrates the capacity to harmonize both objectives, thereby achieving a reduction in both TTT and TE.