Multi-agent modeling and analysis of EV users’ travel willingness based on an integrated causal/statistical/behavioral model

• Main Authors: Juai WU, Yusheng XUE, Dongliang XIE, Kang LI, Fushuan WEN, Junhua ZHAO, Guangya YANG, Qiuwei WU
• Format: Article
• Language: English
• Published: IEEE 2018-05-01
• Series: Journal of Modern Power Systems and Clean Energy
• Subjects: Travel willingness; Questionnaire design; Multi-agent; Experimental economics; Causal analysis
• Online Access: http://link.springer.com/article/10.1007/s40565-018-0408-2
• ISSN: 2196-5625; 2196-5420

Abstract An electric vehicle (EV) centred ecosystem has not yet been formed, the existing limited statistic data are far from enough for the analysis of EV users’ travel and charge behaviors, which however tends to be affected by many certain and uncertain factors. An experimental economics (EE) based simulation method can be used to analyze the behaviors of key participants in a system. However, it is restricted by the system size, experimental site and the number of qualified human participants. Therefore, this method is hard to be adopted for the behavioral analysis of a large number of human participants. In this paper, a new method combining a questionnaire statistics and the EE-based simulation is proposed. The causal relationship is considered in the design of the questionnaires and data extraction, then a multi-agent modeling integration method is introduced in the EE-based simulation, which enables the integration of causal/statistical/behavioral models into the multi-agent framework to reflect the EV users’ travel willingness statistically. The generated multi-agents are used to replace human participants in the EE-based simulation in order to evaluate EV users’ travel demands in different scenarios, and compare the differences of simulated or measured travel behaviors between potential EV users and internal combustion engine (ICE) vehicle users.