Identifying critical links in urban traffic networks: a partial network scan algorithm

Abstract

Purpose – Critical links in traffic networks are those who should be better protected because their removal has a significant impact on the whole network. So, the purpose of this paper is to identify the critical links of traffic networks. Design/methodology/approach – This paper proposes the definition of the critical link for an urban traffic network and establishes mathematical model for determining critical link considering the travellers’ heterogeneous risk-taking behavior. Moreover, in order to improve the computational efficiency, the impact area of a link is quantified, a partial network scan algorithm for identifying the critical link based on the impact area is put forward and the efficient paths-based assignment algorithm is adopted. Findings – The proposed algorithm can significantly reduce the search space for determining the most critical links in traffic network. Numerical results also demonstrate that the structure of efficient paths has significant impact on identifying the critical links. Originality/value – This paper identifies the critical links by using a bi-level programming approach and proposes a partial network scan algorithm for identifying critical links accounting for travellers’ heterogeneous risk-taking behavior.

Identifying Critical Elements of Road Infrastructure Using Cascading Impact Assessment

“…-network robustness index (Scott et al 2006); -method for diagnosis of critical locations in transport infrastructure systems (Taylor, D'Este 2007); -determining critical links in a road network: vulnerability and congestion indicators (Oliveira et al 2014); -method of searching for critical links in traffic network based on link redundancy (Yu et al 2014); -practical method for the calculation of link importance (Rupi et al 2015); -partial network scan algorithm (Yang et al 2016); -methodology for identification of critical infrastructure objects in transport (Dvořák et al 2017); -identification model of urban critical links with macroscopic fundamental diagram theory (Dong et al 2017). The tools and methods listed above were compared using a set of criteria reflecting the defined evaluation conditions, i.e.…”

“…Because of these computational demands, an alternative method was developed. This method uses a partial network scan algorithm based on analysing the length and number of replacement routes for given sections (Yang et al 2016). Another view offers a method based on the link redundancy of a sub-network, namely the availability of replacement routes (Yu et al 2014).…”

Critical links detection in stochastic networks: application to the transport networks

“…The most vital nodes/links (MVN/MVL) detection problem-related research works aim to maintain the networks reliability by detecting the links and nodes whose removal maximally destroys the network’s functions. This topic has received increased attention in recent years (Arulselvan et al , 2009; Shen, Smith and Goli, 2012; Shen, Dinh and Thai, 2012; Shen et al , 2013; Shirdel and Abdolhoseinzadeh, 2016; Yang et al , 2016; Zhou and Wang, 2018). Many variants of metrics to assess the network vulnerability have been proposed among which total pairwise connectivity (Arulselvan et al , 2009; Dinh et al , 2010; Shen et al , 2013), number of connected components (Shen, Smith and Goli, 2012; Shen, Dinh and Thai, 2012) and shortest path length (Bar-Noy et al , 1995; Corley and David, 1982; Scott et al , 2006; Ukkusuri and Yushimito, 2009).…”

“…Almost all these works assess the criticality of links and nodes on the whole network without considering local vision of the problem, what call into question their efficiency, mainly on large size networks. For that reason, in one of the most relevant recent work, Yang et al (2016) proposed a bi-level programming approach, using a partial network scan algorithm, for critical link detection in urban traffic networks, considering the travelers’ heterogeneous risk-taking behavior. The proposed algorithm consists on computing the efficient path based on restricting the effect of each link to its quantified impact area, what can significantly reduce the search space.…”

“…Due to their crucial role in the evaluation of network’s robustness, critical links have been widely studied in the literature (Bocchini and Frangopol, 2011; de Oliveira et al , 2014; Sullivan et al , 2010; Taylor and D′Este, 2007; Ukkusuri and Yushimito, 2009; Yang et al , 2016; Zhou and Wang, 2018). The identification and protection of critical links require efficient and proactive approaches to optimize transport plans in both normal and disaster situations.…”