2,612 research outputs found
Traffic at the Edge of Chaos
We use a very simple description of human driving behavior to simulate
traffic. The regime of maximum vehicle flow in a closed system shows
near-critical behavior, and as a result a sharp decrease of the predictability
of travel time. Since Advanced Traffic Management Systems (ATMSs) tend to drive
larger parts of the transportation system towards this regime of maximum flow,
we argue that in consequence the traffic system as a whole will be driven
closer to criticality, thus making predictions much harder. A simulation of a
simplified transportation network supports our argument.Comment: Postscript version including most of the figures available from
http://studguppy.tsasa.lanl.gov/research_team/. Paper has been published in
Brooks RA, Maes P, Artifical Life IV: ..., MIT Press, 199
Connected Spatial Networks over Random Points and a Route-Length Statistic
We review mathematically tractable models for connected networks on random
points in the plane, emphasizing the class of proximity graphs which deserves
to be better known to applied probabilists and statisticians. We introduce and
motivate a particular statistic measuring shortness of routes in a network.
We illustrate, via Monte Carlo in part, the trade-off between normalized
network length and in a one-parameter family of proximity graphs. How close
this family comes to the optimal trade-off over all possible networks remains
an intriguing open question. The paper is a write-up of a talk developed by the
first author during 2007--2009.Comment: Published in at http://dx.doi.org/10.1214/10-STS335 the Statistical
Science (http://www.imstat.org/sts/) by the Institute of Mathematical
Statistics (http://www.imstat.org
Global efficiency and network structure of urban traffic flows: A percolation-based empirical analysis
Making the connection between the function and structure of networked systems
is one of fundamental issues in complex systems and network science. Urban
traffic flows are related to various problems in cities and can be represented
as a network of local traffic flows. To identify an empirical relation between
the function and network structure of urban traffic flows, we construct a
time-varying traffic flow network of a megacity, Seoul, and analyze its global
efficiency with a percolation-based approach. Comparing the real-world traffic
flow network with its corresponding null-model network having a randomized
structure, we show that the real-world network is less efficient than its
null-model network during rush hour, yet more efficient during non-rush hour.
We observe that in the real-world network, links with the highest betweenness
tend to have lower quality during rush hour compared to links with lower
betweenness, but higher quality during non-rush hour. Since the top betweenness
links tend to traverse the entire network, their congestion has a stronger
impact on the network's global efficiency. Our results suggest that urban
traffic congestion might arise when such backbone links are severely congested
rather than the whole system is slowing down.Comment: 7 pages, 4 figure
Robustness and Closeness Centrality for Self-Organized and Planned Cities
Street networks are important infrastructural transportation systems that
cover a great part of the planet. It is now widely accepted that transportation
properties of street networks are better understood in the interplay between
the street network itself and the so called \textit{information} or
\textit{dual network}, which embeds the topology of the street network
navigation system. In this work, we present a novel robustness analysis, based
on the interaction between the primal and the dual transportation layer for two
large metropolis, London and Chicago, thus considering the structural
differences to intentional attacks for \textit{self-organized} and planned
cities. We elaborate the results through an accurate closeness centrality
analysis in the Euclidean space and in the relationship between primal and dual
space. Interestingly enough, we find that even if the considered planar graphs
display very distinct properties, the information space induce them to converge
toward systems which are similar in terms of transportation properties
Two-Hop Connectivity to the Roadside in a VANET Under the Random Connection Model
We compute the expected number of cars that have at least one two-hop path to
a fixed roadside unit in a one-dimensional vehicular ad hoc network in which
other cars can be used as relays to reach a roadside unit when they do not have
a reliable direct link. The pairwise channels between cars experience Rayleigh
fading in the random connection model, and so exist, with probability function
of the mutual distance between the cars, or between the cars and the roadside
unit. We derive exact equivalents for this expected number of cars when the car
density tends to zero and to infinity, and determine its behaviour using
an infinite oscillating power series in , which is accurate for all
regimes. We also corroborate those findings to a realistic situation, using
snapshots of actual traffic data. Finally, a normal approximation is discussed
for the probability mass function of the number of cars with a two-hop
connection to the origin. The probability mass function appears to be well
fitted by a Gaussian approximation with mean equal to the expected number of
cars with two hops to the origin.Comment: 21 pages, 7 figure
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