Assessing the Demand Vulnerability of Equilibrium Traffic Networks via Network Aggregation

Abstract

Studies of network vulnerability typically focus on changes to the supply side; whether considering a degradation of link capacity or complete link failure. However, the level of service provided by a transport network is also vulnerable to increases in travel demand, with the consequent congestion causing additional delays. Traffic equilibrium models can be used to evaluate the influence of travel demand on levels of service when interest is restricted to only a small number of pre-specified demand scenarios. A demandvulnerability analysis requires understanding the impact of unknown future changes to any possible combination of OD demands. For anything but the smallest networks, this cannot be accomplished by recomputing network equilibrium at all possible demand settings. We require a representation of the functional relationship between demands and levels of service, avoiding the need to re-evaluate the equilibrium model. This processof collapsing the demand and network representations onto a single, coarse-level network with explicit functional relationshipsis referred to here as 'network aggregation'. We present an efficient method for network aggregation for networks operating under Stochastic User Equilibrium (SUE). In numerical experiments, we explore the nature and extent of the aggregation errors that may arise.

Vulnerability and resilience of transport systems – A discussion of recent research

“…Terminal or connectivity reliability is the probability that there is still a connection between a pair of nodes when one or more links are removed (e.g., Bell and Iida, 1997;Wakabayashi and Iida, 1992); travel time reliability is the probability that a trip can be completed within a specified time interval (e.g., Clark and Watling, 2005;Yang et al, 2000); and capacity reliability is the probability that a network can accommodate a specified level of travel demand (e.g., Chen et al, 2002;Yang et al, 2000). Connors and Watling (2014) introduce the related concept of demand vulnerability to capture the impact of unknown future changes in demand on level of service and how it could be analysed at a comprehensive level by network aggregation.…”

Robustness of airline route networks

“…In future studies the passenger flux could be taken into account and, as a result, an interpretation of the traffic loss caused by the closure of airports may arise. Passenger flows are also central to assess other kinds of disruptions, such as demand vulnerabilities (Connors and Watling, 2014), that can be tackled via hub flow optimization (OKelly, 2010). A similar result would be expected because most central airports are those that concentrate a higher volume of aerial traffic in terms of flights and passengers.…”

Stochastic user equilibrium with equilibrated choice sets: Part II – Solving the restricted SUE for the logit family

“…An alternative computational approach that might be pursued in the future could be to reduce the 'solution space' through techniques proposed for network aggregation (e.g. Connors and Watling, 2015).…”