Multiobjective network design for emission and travel-time trade-off for a sustainable large urban transportation network
Existing optimal road-network capacity-expansion models are based on minimizing travel time and rarely consider environmental factors such as vehicular emissions. In this study we attempt to solve such a transportation network design problem when the planner is environment conscious and thereby tries to minimize health-damage cost due to vehicular emissions along with total system travel time while performing optimal capacity expansion. This problem can be formulated as a multiobjective optimization model which minimizes emissions in addition to travel time, and under budget constraints. A prerequisite for this model is an accurate estimation of vehicle emissions due to changes in link capacities. Since the current practice of estimation of vehicular emissions by aggregate emission factors does not account for the improved speeds resulting from capacity improvements, speed-dependent emission functions for various transport modes and pollutants are used in this study. These functions help in calculating emission factors for use in the proposed model. The model uses a nondominated sorting genetic algorithm as the optimization tool to solve the network design problem. The model is tested on a small hypothetical network and solved for a real large-sized network in India taking into account three pollutants and five transport modes. The Pareto-optimal solutions generated can act as trade-offs between total emissions and total system travel time to account for the planner’s desired objectives. Also, reduction in travel time as well as in emissions supports the present model compared with the single-objective model.
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