Route-choice management with optimal dynamic pricing in urban large-scale networks

Abstract

Traffic management with congestion pricing is a measure for mitigating traffic congestion in a protected corridor. Hence, the level of service in a city center (i.e., the protected corridor) increases and leads to a reduction in travel times and travel delays. So far, implementations in the field are restricted to static pricing, i.e., the price is fixed and not responsive to the prevailing regional traffic conditions. Dynamic pricing overcomes these limitations but also influences in real time the user’s route choices. Consequently, this measure can be utilized to aim for optimal traffic distribution in the network. The proposed framework models a large-scale network where every region is considered as homogeneous, allowing for application of Macroscopic Fundamental Diagram (MFD). We compute Dynamic System Optimum (DSO) and Dynamic User Equilibrium (DUE) of the macroscopic model by formulating a linear optimization problem and utilizing the Dijkstra algorithm and a multinomial Logit model, respectively. Finally, we derive the optimal pricing functions for an exogenous demand scenario by applying the concept of elasticities. We test our framework to a case study in Zurich, Switzerland, and showcase the optimal price functions for the multi-region model.