Stochastic Approximations for the Macroscopic Fundamental Diagram of Urban Networks

By Jorge A. Laval, Felipe Castrillón, Yi Zhou. 2015

137 citations recorded by the source corpus.

This paper proposes a theory for estimating the Macroscopic Fundamental Diagram (MFD) on inhomogeneous corridors and networks using probabilistic methods. By exploiting asymmetry property of the stochastic MFD, whereby it exhibits identical probability distributions free-flow and congestion, it is found that the network MFD depends mainly on two dimensionless parameters: the mean block length two green ratio and the mean red to green ratio. Special consideration is given to corridors with short blocks, which can severely reduce network capacity. The theory is validated with an exact traffic simulation and with the empirical data from the city of Yokohama.

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

View Paper: https://www.semanticscholar.org/paper/bc483f66190ed7cdda6abde1453a134a0e74ce4b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Control and Systems Engineering

  1. Ludovic Leclercq
  2. Jorge A. Laval
  3. G. Mariotte
  4. Zuduo Zheng

In Safety, Risk, Reliability and Quality

  1. Jorge A. Laval
  2. Ludovic Leclercq

In Transportation

  1. Ludovic Leclercq
  2. Jorge A. Laval
  3. G. Mariotte
  4. Zuduo Zheng

Citations in the corpus