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To convert HOV (high-occupancy vehicle) lanes to HOT (high-occupancy toll) lanes, it is necessary to evaluate the relevant benefits to drivers, to highway maintenance, to traffic management, and to the whole society under various combinations of tolls, motorists’ perception error, and travel demand. This paper assesses the benefit and effect of an HOV/HOT lane project on the I-394 corridor network in the Twin Cities by using an analytical multiclass stochastic dynamic transportation network model with Monte Carlo simulation and the method of successive averages. Specifically, the effects of various toll schemes for HOT lane design and operations are investigated. The results are analyzed, yielding useful insights for the design and evaluation of HOT lanes. [ABSTRACT FROM AUTHOR]

This paper addresses the road toll pricing and capacity investment problem in a congested road network in a multicriteria decision-making framework. A goal programming approach is used in which the following four major goals are considered: (1) cost recovery, (2) service level, (3) environmental, and (4) equity. The multiobjective road toll pricing and capacity investment problem is formulated as a bilevel goal programming model. The upper level of the model aims to minimize the deviations from stated goals for a given priority ranking of the goals, while the lower level is the road users' route choice equilibrium problem. A simulated annealing-based solution algorithm is developed to solve the proposed model. Numerical results show that the priority structure of the goals can significantly affect the road toll pricing and capacity investment decisions. The simulated annealing-based solution algorithm outperforms the sensitivity analysis-based solution algorithm in terms of solution quality. The proposed methodology provides an avenue for understanding the trade-offs among conflicting objectives and for designing a financially and environmentally sustainable transportation system. [ABSTRACT FROM AUTHOR]