Abstract
The availability of refuelling locations for alternative fuel vehicles (AFVs) is an important factor that drivers consider before adopting an AFV; thus, the layout of initial filling stations for AFVs will influence the adoption of AFVs. This paper presents a training system for optimising the layout of initial filling stations for AFVs by linking an agent-based model of the adoption of AFVs with a real city/area's road network, as well as the city/area's social and economic background. In the agent-based model, two types of agents (driver agents and station owner agents) interact with each other in a city/area's road network, stored in a GIS (Geographic Information System). With simulation scenario analyses and a genetic algorithm, the training system presented in this paper can help decision makers determine close-to-optimal layouts for initial AFV filling stations. This paper also presents a case study of the application of the training system that analyses the layout of fast-charging or battery-changing stations for the promotion of electric vehicles adoption in Shanghai.
Highlights
1.1 With increasing concerns regarding climate change and the depletion of fossil fuels, developing alternative fuel vehicles (AFVs) has become a national technology strategy for many countries, e.g. (China's State Council 2012; US Department of Energy 2013)
To promote the adoption of AFVs, governments must organise some initial filling stations as the "seeds" for technological learning. Where should these initial filling stations be located so that they can induce a successful diffusion of AFVs? It is difficult to answer this question with traditional operational approaches and equilibrium analysis because the adoption of AFVs is a complex process that involves various heterogeneous actors interacting with each other
It is difficult to identify an optimal layout of initial filling stations for alternative fuel vehicles in a city/area with traditional operational optimisation or equilibrium analysis
Summary
To promote the adoption of AFVs, governments must organise some initial filling stations as the "seeds" for technological learning. Where should these initial filling stations be located so that they can induce a successful diffusion of AFVs? It is possible that a leading company could set initial filling stations for its own business; for example, Tesla has started constructing initial recharging stations for its electric vehicles in the US[1]. In this case, the decision makers are the company's managers
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