Multiobjective decision making for traffic assignment

The use of traffic assignment methods with multiobjective decision making to remedy the shortcomings of conventional traffic assignment methods is discussed. The optimal flow patterns are determined using three objectives: total travel time for road users; air pollution for nonusers; and travel distance for government. By using multiobjective decision making and nonlinear programming techniques, a series of noninferior solutions is generated. By combining an eigenvector weighting method with pairwise comparison, a compromise solution for the flow pattern is obtained. As an application example the Taipei network system is discussed. The results show that if other nontraffic-related factors are taken into account, the multiobjective traffic assignment approach is more reasonable and suitable than conventional approaches