Planning for electric taxi charging system from the perspective of transport energy supply chain: A data-driven approach in Beijing
Conference Paper, Proceedings of IEEE Transportation Electrification Conference and Expo, Asia-Pacific (ITEC Asia-Pacific), August, 2017
Abstract
Administration in big cities is strongly promoting electric taxis (ETs) by providing purchasing subsidies, accessorial public facilities and many other encouraging policies. However, how to allocate the limited resources to optimize the benefits brought by ETs remains a headache for most researchers. Applying data mining technology, this research gathers real-time vehicle trajectory data of 39,053 urban conventional taxis (CTs) and 408 suburban ETs in Beijing for 4 weeks to extract the model of customers' travel demand and ET driving patterns. Based on the transport energy supply chain derived from Global Positioning System (GPS) data, we develop a data-driven method to design ET charging infrastructure in the near future.
BibTeX
@conference{Jia-2017-131440,author = {Yinghao Jia and Huimiao Chen and Jiaoyang Li and Fang He\ and Meng Li and Zechun Hu and Zuo-Jun Max Shen},
title = {Planning for electric taxi charging system from the perspective of transport energy supply chain: A data-driven approach in Beijing},
booktitle = {Proceedings of IEEE Transportation Electrification Conference and Expo, Asia-Pacific (ITEC Asia-Pacific)},
year = {2017},
month = {August},
}
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