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- Title
An Agent-Based Training System for Optimizing the Layout of AFVs' Initial Filling Stations.
- Authors
Tieju Ma; Jiangjiang Zhao; Shijian Xiang; Ya Zhu; Peipei Liu
- 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.
- Subjects
SHANGHAI (China); CHINA; ALTERNATIVE fuel vehicles; GEOGRAPHIC information systems; SERVICE stations
- Publication
Journal of Artificial Societies & Social Simulation, 2014, Vol 17, Issue 4, p1
- ISSN
1460-7425
- Publication type
Article
- DOI
10.18564/jasss.2570