Integrated Bilevel Model to Explore Interaction between Land Use Allocation and Transportation

Abstract

The purpose of this paper is to develop a bilevel integrated dynamic model—a combination of an upper land use allocation model and a lower transportation model—to quantify the interaction between different land use allocation strategies and the transportation system. To manage the dynamic land use change in spatial and temporal dimensions, the upper-level model uses cellular automata to capture the spatial attributes of land use change, whereas the bid–rent agent model focuses on household location choice behavior. The cell-based land allocation strategy and residential location choice generated in the upper-level model are fed into the lower-level model to reflect new transportation demand, travel cost, and transportation accessibility. Then, the travel cost and transportation accessibility produced in the lower-level model are fed back into the upper-level model. To optimize land use allocation strategy, a combination of a genetic algorithm and a Frank–Wolfe algorithm is used to minimize transportation system costs. Numeric analysis of a fictitious urban area showed that the optimal land allocation with the bilevel model significantly enhanced transportation efficiency and reduced the system cost of transportation by 30.8% to 90.2%.