Robust network pricing and system optimization under combined long-term stochasticity and elasticity of travel demand

摘要: Network pricing serves as an instrument for congestion management, however, agencies and planners often encounter problems of estimating appropriate toll prices. Tolls are commonly estimated a single-point deterministic travel demand, which may lead to imperfect policy decisions due inherent uncertainties in future demand. Previous research has addressed the issue demand uncertainty context, but elastic nature along with its not been explicitly considered. Similarly, interactions between elasticity have characterized. This study addresses these gaps proposes framework estimate nearest optimal first-best tolls under long-term stochasticity We show first that deterministic-elastic stochastic-elastic cases coincide when cost functions linear, set equilibrium paths is constant. These assumptions restrictive, so three larger networks considered numerically, subsequent assessed. The results numerical experiments suggest many cases, combined scenario resemble those known exactly. applications this thus inclusion offsets need considering frameworks.