TY - ELEC
AU - Nogal, Maria
AU - Martinez-Pastor, Beatriz
AU - Oâ€™Connor, Alan
AU - Caulfield, Brian
PY - 2015
TI - Dynamic restricted equilibrium model to determine statistically the resilience of a traffic network to extreme weather events
KW - Conference Paper
LA - eng
M3 - Text
AB - Extreme weather events lead transportation systems to critical situations, which imply high
social, economical and environmental costs. Developing a tool to quantify the damage suffered by a traffic
network and its capacity of response to these phenomena is essential to reduce the damage of this hazard
and to improve the system. With this aim, a statistical analysis of the resilience of a traffic network under
extreme climatological events is presented. The resilience of a traffic network is determined by means
of a dynamic restricted equilibrium model together with a travel cost function that includes the effect of
weather on a traffic network. The cost function parameters related to the hazard effect are assumed as
random, following Generalized Beta distributions. Then, the fragility curves of the target traffic network
are defined using the Monte Carlo method and Latin Hypercube sampling. Fragility curves are a useful
tool to analyse of the vulnerability of a traffic network, assisting in the decision-making for the prevention
and response to the extreme weather events.
N2 - Extreme weather events lead transportation systems to critical situations, which imply high
social, economical and environmental costs. Developing a tool to quantify the damage suffered by a traffic
network and its capacity of response to these phenomena is essential to reduce the damage of this hazard
and to improve the system. With this aim, a statistical analysis of the resilience of a traffic network under
extreme climatological events is presented. The resilience of a traffic network is determined by means
of a dynamic restricted equilibrium model together with a travel cost function that includes the effect of
weather on a traffic network. The cost function parameters related to the hazard effect are assumed as
random, following Generalized Beta distributions. Then, the fragility curves of the target traffic network
are defined using the Monte Carlo method and Latin Hypercube sampling. Fragility curves are a useful
tool to analyse of the vulnerability of a traffic network, assisting in the decision-making for the prevention
and response to the extreme weather events.
UR - https://open.library.ubc.ca/collections/53032/items/1.0076055
ER - End of Reference