Network Robustness Index: A new method for identifying critical links and evaluating the performance of transportation networks

Scott, Darren M.; Novak, David C.; Aultman-Hall, Lisa; Guo, Feng

doi:10.1016/j.jtrangeo.2005.10.003

Cited by 408 publications

(247 citation statements)

References 21 publications

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“…Meanwhile Scott et al (2006) employed transport network perfomance indicators to identify the most "critical" or "important" link in the road network. Overall, the use and applicability of each approach appears to be heavily dependent on the scope of the research.…”

Section: Vulnerability Assessment Methods and Indicatorsmentioning

confidence: 99%

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An assessment method for highway network vulnerability

Rashidy

Grant-Muller

2014

Journal of Transport Geography

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This paper introduces a methodology to assess the level of vulnerability of road transport networks. A new technique based on fuzzy logic and exhaustive search optimisation is used to combine vulnerability attributes with different weights into a single vulnerability index for network links, which may be used to measure the impact of disruptive events. The network vulnerability index is then calculated using two different aggregations: an aggregated vulnerability index based on physical characteristics and an aggregated vulnerability index based on operational characteristics. The former uses link physical properties such as its length and the number of lanes, whilst the latter reflects aspects of the network flow. The application of the methodology on a synthetic network (based on Delft city, Netherland) demonstrates the ability of the technique to estimate variation in the level of vulnerability under different scenarios. The method also allows exploration of how variation in demand and supply impact on overall network vulnerability, providing a new tool for decision makers to understand the dynamic nature of vulnerability under various events. The method could also be used as an evaluation tool to gauge the impact of particular policies on the level of vulnerability for the highway network and highlight weaknesses in the network.

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Section: Vulnerability Assessment Methods and Indicatorsmentioning

confidence: 99%

“…This principle is also known as the user optimum (Wardrop, 1952). The suitability of the UE method for identifying the most critical link is based on two issues (Scott 2006). Firstly, the ability of the method to take into account the level of link functionality by allocating the user to the best route in terms of travel time, i.e.…”

Section: Case Studymentioning

confidence: 99%

An assessment method for highway network vulnerability

Rashidy

Grant-Muller

2014

Journal of Transport Geography

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“…Several previous studies (Weidner 1996;Horner and O'Kelly 2001;Yerra and Levinson 2005;Scott et al 2006;Miyagawa 2011) in this area show that transportation networks (road, air, etc. ) tend to self-organize into a hierarchical pattern in which some links attract more traffic/ users, receive proper maintenance, and are gradually expanded, while other links are less popular, poorly maintained, and may eventually be abandoned.…”

Section: Introductionmentioning

confidence: 93%

A model of the rise and fall of roads

Zhang

Levinson

2016

JTLU

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This paper analyzes the relationship between network supply and travel demand and describes a road development and degeneration mechanism microscopically at the link (road-segment) level. A simulation model of transportation network dynamics is developed, involving iterative evolution of travel demand patterns, network revenue policies, cost estimation, and investment rules. The model is applied to a real-world congesting network for Minneapolis-St. Paul, Minnesota (Twin Cities), which comprises nearly 8000 nodes and more than 20,000 links, using network data collected since 1978. Four experiments are carried out with different initial conditions and constraints, the results of which allow us to explore model properties such as computational feasibility, qualitative implications, potential calibration procedures, and predictive value. The hypothesis that road hierarchy is an emergent property of transportation networks is corroborated and the underlying reasons discovered. Spatial distribution of capacity, traffic flow, and congestion in the transportation network is tracked over time. Potential improvements to the model, in particular, and future research directions in transportation network dynamics, in general, are also discussed.

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“…Rosenkrantz et al [16] suggest the idea of a ''StructureBased Resilience Matrix'' to measure the vulnerability/resilience of networks' components. Scott et al [17] used network flows, link capacity and network topology to develop a network robust index measure. Leu et al [18] used a network analysis to measure the robustness considering physical features of the network.…”

Section: Literature Reviewmentioning

confidence: 99%

Identifying Achilles-heel roads in real-sized networks

et al. 2017

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Ensuring a minimum operational level of road networks in the presence of unexpected incidents is becoming a hot subject in academic circles as well as industry. To this end, it is important to understand the degree to which each single element of the network contributes to the operation and performance of a network. In other words, a road can become an ''Achilles-heel'' for the entire network if it is closed due to a simple incident. Such insight of the detrimental loss of the closure of the roads would help us to be more vigilant and prepared. In this study, we develop an index dubbed as Achilles-heel index to quantify detrimental loss of the closure of the respective roads. More precisely, the Achilles-heel index indicates how many drivers are affected by the closure of the respective roads (the number of affected drivers is also called travel demand coverage). To this end, roads with maximum travel demand coverage are sorted as the most critical ones, for which a method-known as ''link analysis''-is adopted. In an iterative process, first, a road with highest traffic volume is first labeled as ''target link,'' and second, a portion of travel demand which is captured by the target link is excluded from travel demand. For the next iteration, the trimmed travel demand is then assigned to the network where all links including the target links run on the initial travel times. The process carries on until all links are labeled. The proposed methodology is applied to a largesized network of Winnipeg, Canada. The results shed light on also bottleneck points of the network which may warrant provision of additional capacity or parallel roads.

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Network Robustness Index: A new method for identifying critical links and evaluating the performance of transportation networks

Cited by 408 publications

References 21 publications

An assessment method for highway network vulnerability

An assessment method for highway network vulnerability

A model of the rise and fall of roads

Identifying Achilles-heel roads in real-sized networks

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