Robust Transport Network Capacity Planning with Demand Uncertainty

This paper proposes a robust transport network capacity planning model (RTNCP) with demand uncertainty. The stochastic demand is assumed to follow a normal distribution with travellers' route choice behaviour following Probit Stochastic User Equilibrium (SUE). The network reserve capacity is measured by potential increase in both mean and standard deviation of the base stochastic demand. The objective of the RTNCP is, thus, to optimise the link capacity expansion so as to maximize the weighted sum of mean and standard deviation perturbed demands without violating the link capacity and budget constraints. The paper applies the implicit programming method to solve the optimization problem. The sensitivity analysis approach is adopted to derive the derivative of the equilibrium path choice probability with respect to design variables. The proposed model and algorithm are then applied to a test network.