Properties of a well-defined Macroscopic Fundamental Diagram for urban traffic

By Nikolaos Geroliminis, Jie Sun. 2011

541 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Safety, Risk, Reliability and Quality, Transportation

View Paper: https://www.semanticscholar.org/paper/a82dadc436b4d3d330ef121efbf1617b7006804a

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In Control and Systems Engineering

In Safety, Risk, Reliability and Quality

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Citations in the corpus

Optimal Perimeter Control for Two Urban Regions With Macroscopic Fundamental Diagrams: A Model Predictive Approach (2013, background): “Other investigations of MFD using empirical or simulated data can be found in [5]–[8] and other papers, whereas routing strategies that are based on MFD can be found in [9].”
Perimeter and boundary flow control in multi-reservoir heterogeneous networks (2013, background): “Recent works (Mazloumian et al., 2010; Geroliminis and Sun, 2011; Daganzo et al., 2011; Knoop et al., 2012; Saberi and Mahmassani, 2012) have identified the spatial distribution of vehicle density in the network as one of the key components that affect the scatter of an MFD and its shape.”
Exploiting the fundamental diagram of urban networks for feedback-based gating (2012, background): “In simulated environments, where different signal control strategies are tested, this homogeneity condition may call for activation of a dynamic traffic assignment device to reduce possible transient phenomena, such as a hysteresis between network filling and emptying data (Aboudolas et al., 2010; G”
Dynamics of heterogeneity in urban networks: aggregated traffic modeling and hierarchical control (2015, methodology): “More homogeneous networks can improve both the average travel time (because of higher network outflow), and the travel time reliability, as shown by Saberi and Mahmassani (2013).”
On the spatial partitioning of urban transportation networks (2012, background): “Geroliminis and Sun (2011) have noticed from the real network of Yokohama that a low scatter MFD exists even if there is some variance in the distribution of congestion (coefficient of variation in link density, i.e. dimensionless standard deviation divided by the mean, was around 0.25).”
A Bathtub Model of Downtown Traffic Congestion (2013, background): “If there are late departures, there is a discontinuous decrease in the departure rate at t = 0, and t solves d(t) = 0 from (14).”
Exploring Properties of Networkwide Flow–Density Relations in a Freeway Network (2012, methodology): “phenomena in freeway networks is the different spatial distribution of congestion for the same level of average network density (9, 10).”
Hysteresis Phenomena of a Macroscopic Fundamental Diagram in Freeway Networks (2011, background): “…that heterogeneity has a strong impact on the shape/scatter of an MFD. Recent findings from empirical and simulated data for arterial networks (Geroliminis and Sun, 2011; Mazloumian et al., 2010) have identified the spatial distribution of vehicle density in the network as one of the key…”
Robust Constrained Control of Uncertain Macroscopic Fundamental Diagram Networks (2015, background): “…for the existence of well-defined MFDs for homogeneous urban networks with small variance of link densities Godfrey (1969); Daganzo (2007); Geroliminis and Daganzo (2008); Geroliminis and Sun (2011b); Buisson and Ladier (2009); Ji et al. (2010); Mazloumian et al. (2010); ∗ Corresponding author.”