Single-Point Approximations for Traffic Equilibrium Problem under Uncertain Demand

The focus of this study is on developing solutions for the traffic equilibrium problem (TEP) when origin-destination demand is assumed to be uncertain. Instead of developing and solving an expensive stochastic solver, it proposes single-point approximate measures that provide a reasonably good estimate of the network performance. Seven approximation schemes that utilize the deterministic TEP to account for uncertain demand and illustrate how these approaches can be used to solve the problem are proposed. The performance of the different approximation measures on different demand distributions for the Sioux Falls, South Dakota, network is reported, and a consistent approximation scheme is identified that performs well for the problem. Such an approximation scheme can be used in solving the TEP accounting for stochastic demand when computational resources are scarce or when a stochastic solver is unavailable.