[Turkmath:6774] Gebze Teknik Üniversitesi Matematik Bölümü Genel Seminerleri

[GTU Mathematics]

Sayin Liste Uyeleri,

Gebze Teknik Üniversitesi (GTU) Matematik Bölümü Genel Seminerleri
kapsamında, 22 Kasım Cuma günü saat 14:00'te Dr. Anıl Yazıcı (Stony Brook
Üniversitesi) bir seminer verecektir. Seminerin detayları aşağıda olup tüm
ilgilenenler davetlidir.

Saygılarımızla.

Dear all,

There will be a seminar in Gebze Technical University (GTU) on 22nd of
November by Dr. Anıl Yazıcı (Stony Brook University).

Time and place: At 14:00 in Department of Mathematics, Lecture Amphi 2

Title: Link Criticality Index (LCI) for Analysis of Large Transportation
Networks

Abstract:  Designing and maintaining resilient and robust transportation
systems require identification of links that are critical for the
functionality of the network. Network scientists have suggested various
topological measures to identify critical network components in multiple
domains such as energy, water supply, telecommunication, social, and
transportation. However, topological criticality measures usually do not
conform to traffic flow dynamics (e.g., non-linear link performance
functions) and they do not necessarily produce realistic results for
road transportation
networks. In order to overcome this issue, researchers incorporate traffic
characteristics (travel time, link flow, etc.) into criticality metrics,
mostly through traffic assignment. The studies that employ traffic
assignment generally utilize a network performance measure (e.g., total
system travel time) for the complete network, remove each link one by one,
re-run traffic assignment and calculate the selected network performance
measure for each link removal, and identify each link’s criticality based
on the change in the network performance measure. Such full network scan
approach creates computational burden, especially for large networks. Link
removals can also cause network disconnectivity which makes it problematic
to run traffic assignment. This talk will present the recently developed
Link Criticality Index (LCI) which does not require link removals and can
provide transportation link criticality rankings for large networks with a
single User Equilibrium (UE) traffic assignment. The LCI scores are
calculated based on the link flow changes and link performance functions
during UE iterations. In order to take the alternative OD paths into
account, the links scores are weighted based on the travel time differences
between identified OD paths. Also, to reflect the higher importance of links
which serve multiple ODs (or higher demand ODs), demand weights are used.
The LCI was tested on well-known large transportation test networks and
compared with other criticality measures. The findings showed that LCI
successfully
provides balanced link criticality rankings with respect to network
connectivity and redundancy as well as the network flow conditions. Due to
elimination of link removals, the LCI runtime is considerably shorter than
comparable traffic assignment based approaches, i.e., in the order of the
number of links in the network. The inclusion of network topology and
demand characteristics, and shorter runtime make the LCI an appealing
approach for transportation link criticality analysis.
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