To understand the physics of urban mobility, traffic dynamics of multimodal urban networks need to be analyzed under many different scenarios, including various network properties. To this end, an aggregated model for multimodal systems, following the concept of the three-dimensional bi-modal macroscopic fundamental diagram (3D-MFD), can be used to investigate the effects of network topology and configuration, road space allocation and traffic signal control in the multimodal traffic performance.
Provided with the developed modeling tools, smart control approaches on space allocation and traffic signal control will then be proposed, tested, and optimized. At network level, perimeter flow control algorithms, which integrate the treatment of public transport priority, will be developed to improve the global multimodal performance. In addition, and to realize the network-level control actions, we will also focus on the local level to determine where and how to control traffic signals.
The proposed research will provide valuable pragmatic tools to implement some of the suggested approaches in the real world. Both, policy makers and practitioners should be able to utilize these quantitative tools to analyze, evaluate, and propose different traffic management strategies that address the actual needs of any given network. Ultimately, this project aims at the promotion of multimodality and sustainable mobility in urban transportation systems for everybody.