Accessibility is a fundamental concept in transportation analysis and urban planning. Typically, accessibility refers to the ‘ease’ of reaching opportunities for activities and services and can be used to assess the performance of a transportation and urban system. In this paper, we present network-based accessibility measures for assessing vulnerability of degradable transportation networks. The network-based accessibility measures consider the consequence of one or more link failures in terms of network travel time or generalized travel cost increase as well as the behavioral responses of users due to the failure in the network. To model different dimensions of travel behavioral responses, a combined travel demand model is adopted to estimate the long-term equilibrium network condition due to network disruptions. Numerical examples are conducted to demonstrate the feasibility of the proposed vulnerability measures for assessing degradable transportation networks. The results indicate that the accessibility measures derived from the combined travel demand model are capable of measuring the consequences of both demand and supply changes in the network and have the flexibility to reflect the effects of different travel choice dimensions on the network vulnerability. Copyright Springer Science+Business Media, LLC 2007Vulnerability analysis, Combined travel demand model, Accessibility, Random utility,

Equity issues and demand uncertainty are two important issues in the network design problem (NDP). Spatial equity in NDP is concerned with the benefit distribution among network users. By considering demand uncertainty, a more realistic evaluation of the network performance given a network improvement plan can be obtained. Two stochastic models that consider both spatial equity and demand uncertainty are formulated: an expected-value model and a chance-constrained model. Both models are solved by a simulation-based genetic algorithm procedure. The genetic algorithm is used to solve NDP, and stochastic simulation is used to simulate the demand uncertainty. The results of numerical experiments are provided to demonstrate the significance of the equity issue and demand uncertainty in NDP.

This paper aims to provide a state-of-the-art review of the transport network design problem (NDP) under uncertainty and to present some new developments on a biobjective reliable network design problem (BORNDP) model that explicitly optimizes the capacity reliability and travel time reliability under demand uncertainty. Both are useful performance measures that can describe the supply-side reliability and demand side reliability of a road network. A simulation-based multi-objective genetic algorithm (SMOGA) solution procedure, which consists of a traffic assignment algorithm, a genetic algorithm, a Pareto filter, and a Monte-Carlo simulation, is developed to solve the proposed BORNDP model. A numerical example based on the capacity enhancement problem is presented to demonstrate the tradeoff between capacity reliability and travel time reliability in the NDP.

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