Information and Dynamics in Urban Traffic Networks
Author(s)
Petri, Giovanni
Type
Thesis
Abstract
The study of complex systems has intensified in recent years. Researchers
from many different disciplines have realised that the study of systems
possessing a large number of degrees of freedom interacting in a non-linear
way can offer insights into problems in engineering, biology, economics
and many other fields besides. Among the themes in complexity, we focus
here the issues of congestion and congestion emergence in the context of
urban networks, with particular reference to the effects of dissemination of
information about the system’s status. This topic is of great relevance today,
due to the increasing availability of real-time information about traffic
conditions and the large diffusion of personal devices that allow travellers
to access such information.
Through the analysis of a few simple models of information propagation
in urban environment, we uncover that, contrarily to the naïve expectation,
complete information is often detrimental to the global performance of the
urban traffic network. Indeed, global or long-range dissemination induces
correlations in the systems that become a source for spatial disorder, making
the system more prone to the emergence of congested states and pushing
it away from its Wardrop equilibrium. The models we study range
from simple flow models on network to complete agent-based simulations
on real-world networks with interacting agents and dynamical information.
We then analyse real data, coming from London’s network of traffic detectors.
We confirm that the heterogeneity in the distribution of traffic flow
and occupancies across the network reduces its performances, consistently
with the results obtained for the information propagation models. In addition,
we find a rich phenomenology strikingly similar to the one found in
critical self-organised systems. Indeed, we measure power-law correlation functions and 1/f power spectra, hinting to long spatial and temporal effects
in the traffic flow, and confirm this result through the community detection
analysis of the detectors’ correlation network, which showing that
the whole urban area behaves as a single large chunk. We conclude discussing
the origin of these features and how they can be used to improve
the network performances.
from many different disciplines have realised that the study of systems
possessing a large number of degrees of freedom interacting in a non-linear
way can offer insights into problems in engineering, biology, economics
and many other fields besides. Among the themes in complexity, we focus
here the issues of congestion and congestion emergence in the context of
urban networks, with particular reference to the effects of dissemination of
information about the system’s status. This topic is of great relevance today,
due to the increasing availability of real-time information about traffic
conditions and the large diffusion of personal devices that allow travellers
to access such information.
Through the analysis of a few simple models of information propagation
in urban environment, we uncover that, contrarily to the naïve expectation,
complete information is often detrimental to the global performance of the
urban traffic network. Indeed, global or long-range dissemination induces
correlations in the systems that become a source for spatial disorder, making
the system more prone to the emergence of congested states and pushing
it away from its Wardrop equilibrium. The models we study range
from simple flow models on network to complete agent-based simulations
on real-world networks with interacting agents and dynamical information.
We then analyse real data, coming from London’s network of traffic detectors.
We confirm that the heterogeneity in the distribution of traffic flow
and occupancies across the network reduces its performances, consistently
with the results obtained for the information propagation models. In addition,
we find a rich phenomenology strikingly similar to the one found in
critical self-organised systems. Indeed, we measure power-law correlation functions and 1/f power spectra, hinting to long spatial and temporal effects
in the traffic flow, and confirm this result through the community detection
analysis of the detectors’ correlation network, which showing that
the whole urban area behaves as a single large chunk. We conclude discussing
the origin of these features and how they can be used to improve
the network performances.
Date Issued
2012-05
Date Awarded
2012-06
Copyright Statement
Attribution NoDerivatives 4.0 International Licence (CC BY-ND)
Advisor
Jensen, Henrik
Polak, John
Publisher Department
Civil and Environmental Engineering
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)