Effects of optimizing externalities using cooperating dynamic traffic management measures on network level

Optimization of traffic network performance using dynamic traffic management (DTM) measures can be viewed as a specific example of solving a network design problem (NDP). Decision variables are the specific settings of DTM measures. DTM measures have been identified as powerful instruments not only to increase network efficiency, but also to improve externalities. As a result, in the optimization the focus is not only on efficiency, but also on climate, air quality, traffic safety, and noise. These assessment criteria are determined using the output of a dynamic traffic assignment model. This results in a dynamic multi-objective NDP, which is solved as a bilevel optimization problem; it results in a Pareto optimal set. This set provides valuable information for the decision-making process, which would not have been available if the compensation principle would have been chosen in advance. Knowledge obtained by optimization of realistic cases can be used to attain knowledge about incorporation of externalities as an objective when optimizing traffic systems using DTM measures. A case study for a realistic network of the city of Almelo shows that the objectives efficiency, climate, and air quality are mainly aligned and mainly opposed to traffic safety and noise. However, there is not a single solution that optimizes all three aligned objectives. Based on the Pareto optimal set, the trade-offs are determined and using cluster analysis the solutions and results are further analyzed for network segments