Optimizing layouts of initial AFV refueling stations targeting different drivers, and experiments with agent-based simulations

•This paper first explores who should be targeted with initial AFV refueling stations.•Then, it explores the diffusion of AFVs with different numbers of these initial stations.•This paper conducts agent-based simulations for the case of Shanghai.•If AFV technologies are mature, drivers in or close to the center should be targeted.•Too many initial AFV refueling stations might result in slow diffusion of AFVs.

The number of refuelling stations for AFVs (alternative fuel vehicles) is limited during the early stages of the diffusion of AFVs. Different layouts of these initial stations will result in different degrees of driver concern regarding refueling and will therefore influence individuals’ decisions to adopt AFVs. The question becomes “what is an optimal layout for these initial stations? Should it target all drivers or just a portion of them, and if so, which portion?” Further, how does the number of initial AFV refueling stations influence the adoption of AFVs? This paper explores these questions with agent-based simulations. Using Shanghai as the basis of computational experiments, this paper first generates different optimal layouts using a genetic algorithm to minimize the total concern of different targeted drivers and then conducts agent-based simulations on the diffusion of AFVs with these layouts. The main findings of this study are that (1) targeting drivers in the city center can induce the fastest diffusion of AFVs if AFV technologies are mature and (2) it is possible that a larger number of initial AFV refueling stations may result in slower diffusion of AFVs because these initial stations may not have sufficient customers to survive. The simulations can provide some insights for cities that are trying to promote the diffusion of AFVs.