Road network planning (or design) problems consist of determining the best investment decisions to be made with regard to the improvement of a road network. In this paper, we propose an optimization model for long-term interurban road network planning where accessibility and robustness objectives are simultaneously taken into account. Three network robustness measures were defined to assess different robustness concerns: network spare capacity; city evacuation capacity; and network vulnerability. The results that may be obtained from the application of the model are illustrated for three random networks. Special attention is given to the implications of adopting each one of the robustness measures upon the optimum solution provided by the model.

This article presents a multiobjective approach to long-term interurban multilevel road network planning. In addition to the efficiency objectives dealt with in most of the literature where the subject is addressed, the approach takes into account robustness and equity objectives. For achieving the objectives, two types of action can be performed: the construction of a new road of a given level; and the upgrading of an existing road to a higher level. The approach is consistent with the planning framework of the highway capacity manual, using the concept of level of service to assess traffic flow conditions. The application of the approach is illustrated for a case study involving the main road network of Poland.

The traditional approach to the road network design problem focuses on the optimization of network efficiency under a given budget. Generally, this leads to the improvement of roads next to the largest population centers, where travel demand is higher. Such results are not consistent with sustainable development principles, since the dissimilarities between the welfare of large and small centers will tend to increase. Nevertheless, equity issues were rarely taken into account in road network design. Moreover, all existing studies rely on a single equity measure. In this paper equity concerns in transportation planning are reviewed briefly, and a comparison of alternative equity measures is presented. Three equity measures were selected and incorporated into an accessibilitymaximization road network design model. The three equity measures reflect different perspectives on equity: accessibility to low-accessibility centers, the dispersion of accessibility values across all centers (Gini coefficient), and the dispersion of accessibility values across all centers and across centers in the same region (Theil index). The implications of adopting each of these equity measures are illustrated through application of the optimization model to three random networks.

An initial attempt is made to quantify vehicle emissions in the Greater Toronto Area (GTA) in Canada by exploiting travel information provided by activity-based 24-h models rather than conventional trip-based models. For this purpose, travel activity inputs to the Canadian version of the MOBILE6.2 model (MOBILE6.2C) are generated by relying on the travel demand modeling capabilities of the Travel Activity Scheduler for Household Agents (TASHA), a next-generation activity-based model of travel demand for the GTA. Additional input data supplied to MOBILE6.2C are obtained from Canadian sources and by running traffic assignment (using EMME/2) on the trip distribution matrix generated by TASHA. The integration of MOBILE6.2 with TASHA has provided estimates of the time of day that vehicle emissions occur. TASHA provides an explicit representation of trip starts and ends, which results in improved engine start emissions. Overall, because TASHA provides a better behavioral framework for modeling travel than conventional trip-based models, it is expected to lead to better emissions estimates. Such an effort also provides insight and experience that will be used later in the integration of TASHA with more advanced emission models, thus refining the reliability of practical tools that can be used to assess the environmental sustainability of policies.