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The current scarcity of public charging infrastructure is one of the major barriers to mass household adoption of electric vehicles (EVs). Many drivers are reluctant to purchase EVs without convenient charging access away from home, but investors are also hesitant to build charging stations without underlying knowledge of EV demand realization. In this paper, an agent-based decision support system is presented for identifying patterns in residential EV ownership and driving activities to enable strategic deployment of new charging infrastructure. The Chicagoland area is used as a case study to demonstrate the model.
Sweda et al. (Thu,) studied this question.
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