The impact of vehicle emissions on the global climate has drawn increasing concern in thepast few decades. Patterns of housing development determine travel behavior in atransportation system, and consequently affect transport-related greenhouse gas emissions. Inthis study, we establish a bi-level model of the relationships among housing allocation, trafficvolume, and CO_2 emissions using a continuum modeling approach. At the lower-level, themodel achieves the user-equilibrium condition of a transport system. At the upper level, themodel optimizes housing allocation to achieve minimum CO_2 emissions. We consider ahypothetical city with one central business district (CBD) and a road network that is denselydistributed outside of the CBD. In the proposed model, several commuter classes withdifferent values of time are considered. The finite element method (FEM), the Newton-Raphson algorithm, and the convex combination approach are applied to solve theconstrained optimization problem established in the bi-level model. A numerical example isgiven to illustrate the efficiency of the proposed bi-level approach and solution algorithm inmodeling transport demand, traffic intensity, and CO_2 emissions with an optimized housingdevelopment pattern.
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