Policy decision making for trade-offs between mobility and equity maximization under environmental capacity constraints: a case study of an integrated multi-objective model

This paper investigates the trade-offs between mobility and equity maximization under environmental capacity constraints by proposing an integrated model for multi-objective policy decision making. The model specifically deals with two systematic objectives: maximization of mobility and equity, which are respectively formulated by the sum of total car ownership and number of trips, and the difference levels among zonal accessibilities. The environmental capacity constraint is specified based on efficiency theory in which the frontier emission under maximum system efficiency is taken as the capacity. To investigate the performance of the proposed model, three types of hypothetical policies (network improvement, population increase and urban sprawl) are designed and the effects of these policy scenarios are simulated using data of Dalian City, China. Results show that the proposed model can be used for representing the trade-offs between mobility and equity based on different policy interventions. Compaed with two extreme cases with a single objective, mobility maximization and equity maximization, the Pareto-optimal solutions provide more options in practice for decision makers. Taking the solution with the minimum car ownership as an example, the policy of urban sprawl yields the most significant improvement in both emission and accessibility among three scenarios.