The MFD and the built environment

A new perspective on traffic problems in towns


Date

2017

Publication Type

Conference Paper

ETH Bibliography

yes

Citations

Altmetric

Data

Abstract

Travel behavior in urban areas has been widely analyzed from the demand side, while the extent to which the infrastructure imposes constraints on such travel behavior and leads to delays and congestion has almost never been studied. For car-based transportation, the recently developed theory of the macroscopic fundamental diagram (MFD) describes the relationship between the accumulation of vehicles and their trip ending rate as a function of the infrastructure, opening the door to new and meaningful studies that address the gap mentioned above. In this paper, we use empirical traffic data from 42 cities around the world to estimate their MFDs, compare them with respect to their functional behavior and the extent of delays, and explain the observed differences as a function of the network topology, e.g. intersection density, average betweeness. We find that the average betweenness centrality in a network seems to be a very clear indicator for the level of traffic performance. This indicates that it is indeed possible to use some topological features to predict traffic performance at the macroscopic level.

Publication status

published

External links

Editor

Book title

Journal / series

Volume

Pages / Article No.

Publisher

IVT, ETH Zurich

Event

6th Symposium of the European Association for Research in Transportation (hEART 2017)

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

MFD; Network topology; Traffic performance

Organisational unit

03521 - Axhausen, Kay W. (emeritus) / Axhausen, Kay W. (emeritus) check_circle
08686 - Gruppe Strassenverkehrstechnik check_circle
02226 - NSL - Netzwerk Stadt und Landschaft / NSL - Network City and Landscape
02655 - Netzwerk Stadt u. Landschaft ARCH u BAUG / Network City and Landscape ARCH and BAUG

Notes

Funding

Related publications and datasets

Is original form of: