A simulation method to generate commute trips—for agent-based modeling on co-diffusion of alternative fuel vehicles and their filling stations

Existing agent-based models of co-diffusion of alternative fuel vehicles and their corresponding filling stations are very stylized. In addition, there is a lack of methodologies for linking such models with a real social and economic background. Aiming at solving this problem, this paper puts forward a method that uses widely available social, economic, and spatial data to generate driver agents’ commute trips, which play an important role in such models. We tested the method with the data of Shanghai and Beijing, two of the largest cities in China, and found the commute times resulting from the method were in accordance with survey results, which validates the potential usefulness of the method.