Existence of urban-scale macroscopic fundamental diagrams: Some experimental findings

Abstract

A field experiment in Yokohama (Japan) reveals that a macroscopic fundamental diagram (MFD) linking space-mean flow, density and speed exists on a large urban area. The experiment used a combination of fixed detectors and floating vehicle probes as sensors. It was observed that when the somewhat chaotic scatter-plots of speed vs. density from individual fixed detectors were aggregated the scatter nearly disappeared and points grouped neatly along a smoothly declining curve. This evidence suggests, but does not prove, that an MFD exists for the complete network because the fixed detectors only measure conditions in their proximity, which may not represent the whole network. Therefore, the analysis was enriched with data from GPS-equipped taxis, which covered the entire network. The new data were filtered to ensure that only full-taxi trips (i.e., representative of automobile trips) were retained in the sample. The space-mean speeds and densities at different times-of-day were then estimated for the whole study area using relevant parts of the detector and taxi data sets. These estimates were still found to lie close to a smoothly declining curve with deviations smaller than those of individual links -and entirely explained by experimental error. The analysis also revealed a fixed relation between the space-mean flows on the whole network, which are easy to estimate given the existence of an MFD, and the trip completion rates, which dynamically measure accessibility.

On the distribution of urban road space for multimodal congested networks

“…Then, for steady state queuing systems P m i ðtÞ ¼ O m i ðtÞ Á L im (Little, 1961) and V m i ðtÞ ¼ def P m i ðtÞ=n m i ðtÞ. Geroliminis and Daganzo (2008) have shown that trip length of cars in downtown Yokohama was a time invariant variable. The average trip length of buses can be easily estimated as buses have fixed routes.…”

“…While various theories have been proposed to macroscopically model urban networks (Godfrey, 1969;Herman and Prigogine, 1979;Mahmassani et al, 1987;Daganzo, 2007), only until recently Geroliminis and Daganzo (2008) demonstrated the existence of a fundamental model (the macroscopic fundamental diagram -MFD) on congestion dynamics of single-mode system with empirical data. This reference showed that (i) an MFD is a plot between network space-mean flow and density, (ii) the MFD is a property of the network itself (infrastructure and control) and not very sensitive to demand, i.e.…”

Network traffic flow optimization under performance constraints

“…Towards this end, the concept of Network Fundamental Diagram, NFD, often called Macroscopic Fundamental Diagram (MFD), has been adopted as a basis for the derivation of tra c control strategies (e.g., Leclercq et al (2014)). The theory was rst proposed in Godfrey (1969) and further developed in Daganzo and Geroliminis (2008) and Helbing (2009) (its application to experimental data is analyzed in Mahmassani et al (1987); Geroliminis and Daganzo (2008); Ampountolas and Kouvelas (2015)). Geroliminis and Sun (2011) further investigated what the properties that a network should satisfy are, so that an MFD with low scatter exists, by again using data from a eld experiment in Yokohama (Japan).…”

“…It is concluded that if two tra c states from two di erent time intervals have the same spatial distribution of link density, then the two time intervals have the same average ow. As a result, the assumption that congestion is evenly distributed across the network made by Geroliminis and Daganzo (2008) is relaxed. Daganzo (2007) rst used the NFD to synthesize a controller that maximizes the network out ow, thus comprising a starting point for using the NFD theory for controlling tra c ow.…”

Modelling of the Interdependence Between Speed and Traffic Flow Density. A Neuro – Fuzzy Logic Approach

“…The paper [5] contains experimental results concerning this interdependence, which were obtained using a combination of detectors in the network and a vehicle fl eet equipped with sensors.…”