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.