Stabilization of city-scale road traffic networks via macroscopic fundamental diagram-based model predictive perimeter control
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Traffic congestion constitutes one of the most frequent, yet challenging, problems to address in the urban space. Caused by the concentration of population, whose mobility needs surpass the serving capacity of urban networks, congestion cannot be resolved ...
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EPFL2021
,
Network-level road traffic control remains a challenging problem. Macroscopic fundamental diagram (MFD) based dynamical models of large-scale urban networks enable development of model predictive perimeter control methods, which represent an efficient cong ...
2020
Traffic congestion is a significant issue in all urban areas with concentration of activities for various city topologies and distribution of population and land use around the world. Developing realistic models that are able to replicate congestion spread ...
Management of road traffic in urban settings remains a challenging problem. Perimeter control schemes proposed to alleviate congestion in large-scale urban networks usually assume noise-free measurements of the traffic state, which is problematic since mea ...
Traffic management for large-scale urban road networks remains a challenging problem. Aggregated dynamical models of city-scale traffic, based on the macroscopic fundamental diagram (MFD), enable development of model-based control schemes for use with the ...
Merging efficiently into roundabouts represents a challenge for autonomous vehicles due to the speed difference between merging traffic flows and the lack of certainty regarding drivers' intent, specially when the road is shared with human drivers and/or i ...
City-level traffic management remains a challenging problem. Model predictive perimeter control approaches employing macroscopic fundamental diagram (MFD) based models of large-scale urban road traffic represent a high-performance solution with substantial ...
