Bicriterion traffic assignment: Basic theory and elementary algorithms

This paper describes a bicriterion equilibrium traffic assignment model that accurately forecasts path choices and consequent total arc flows for a stochastically diverse set of trips. Called T2, it develops around a linear generalized cost model, which generalizes classical traffic assignment by relaxing the value-of-time parameter from a constant to a random variable with an arbitrary probability distribution. For the case where arc time and/or cost are flow dependent, this paper formulates conditions and algorithms for stochastic bicriterion user-optimal equilibrium arc flows, which reflect every trip’s exclusive use of a path that minimizes its particular perception of generalized cost.