The paper investigates a recent and attractive concept in traffic modeling: the urban-scale Macroscopic Fundamental Diagram (MFD), which is able to link space-mean flow, density and speed in an urban area. Specifically, it explores the possibility to derive the diagram for the complex city context of Rome, Italy, in order to give some guidelines for using MFD in traffic management and control applications. To this aim, the study uses real data, specifically loop detectors and floating car data related to May 2013. Results adopting real data confirm what was obtained in previous studies, such as low scatter in the data points generating the MFD and the hysteresis phenomenon linked with the heterogeneity of traffic patterns and congestion. Some criticalities have been also underlined when deriving the MFD from real data. They are mainly due to the spatial and temporal coverage of the information. Finally, a simulation approach based on the dynamic traffic assignment has been tested as mimicking the presence of loop detectors over the entire road network. The urban-scale MFD resulting from the simulation has been adopted as the leading model to forecast the evolution of traffic inside a monitored area and, consequently, define the traffic management actions to be taken. © 2017, Aracne Ed. All rights reserved.
Urban-scale macroscopic fundamental diagram: An application to the real case study of Rome
Valenti, G.;Liberto, C.
2017-01-01
Abstract
The paper investigates a recent and attractive concept in traffic modeling: the urban-scale Macroscopic Fundamental Diagram (MFD), which is able to link space-mean flow, density and speed in an urban area. Specifically, it explores the possibility to derive the diagram for the complex city context of Rome, Italy, in order to give some guidelines for using MFD in traffic management and control applications. To this aim, the study uses real data, specifically loop detectors and floating car data related to May 2013. Results adopting real data confirm what was obtained in previous studies, such as low scatter in the data points generating the MFD and the hysteresis phenomenon linked with the heterogeneity of traffic patterns and congestion. Some criticalities have been also underlined when deriving the MFD from real data. They are mainly due to the spatial and temporal coverage of the information. Finally, a simulation approach based on the dynamic traffic assignment has been tested as mimicking the presence of loop detectors over the entire road network. The urban-scale MFD resulting from the simulation has been adopted as the leading model to forecast the evolution of traffic inside a monitored area and, consequently, define the traffic management actions to be taken. © 2017, Aracne Ed. All rights reserved.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
