ML Anthology

Evaluating Market User Interfaces for Electric Vehicle Charging Using Bid2Charge

Sebastian Stein, Enrico H. Gerding, Adrian Nedea, Avi Rosenfeld, Nicholas R. Jennings
IJCAI 2017 pp. 4939-4943
doi:10.24963/IJCAI.2017/698 /ijcai/2017/stein2017ijcai-evaluating/

Abstract

We consider settings where electric vehicle drivers participate in a market mechanism to charge their vehicles. Existing work typically assumes that participants are fully rational and can report their charging preferences accurately. However, this may not be reasonable in settings with non-experts. To explore this, we design a novel game called Bid2Charge and compare a fully expressive interface that covers the entire space of preferences to two restricted interfaces that offer fewer possible reports. We show that restricting the users' preferences significantly reduces deliberation times while also leading to an increase in utility by up to 70%.

PDF IJCAI Semantic Scholar

Cite

Text

Stein et al. "Evaluating Market User Interfaces for Electric Vehicle Charging Using Bid2Charge." International Joint Conference on Artificial Intelligence, 2017. doi:10.24963/IJCAI.2017/698

Markdown

[Stein et al. "Evaluating Market User Interfaces for Electric Vehicle Charging Using Bid2Charge." International Joint Conference on Artificial Intelligence, 2017.](https://mlanthology.org/ijcai/2017/stein2017ijcai-evaluating/) doi:10.24963/IJCAI.2017/698

BibTeX

@inproceedings{stein2017ijcai-evaluating,
  title     = {{Evaluating Market User Interfaces for Electric Vehicle Charging Using Bid2Charge}},
  author    = {Stein, Sebastian and Gerding, Enrico H. and Nedea, Adrian and Rosenfeld, Avi and Jennings, Nicholas R.},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2017},
  pages     = {4939-4943},
  doi       = {10.24963/IJCAI.2017/698},
  url       = {https://mlanthology.org/ijcai/2017/stein2017ijcai-evaluating/}
}