Publication Cover
Journal of Intelligent Transportation Systems
Technology, Planning, and Operations
Volume 27, 2023 - Issue 2
516
Views
1
CrossRef citations to date
0
Altmetric
Articles

Learning electric vehicle driver range anxiety with an initial state of charge-oriented gradient boosting approach

&
Pages 238-256 | Received 08 Dec 2020, Accepted 19 Nov 2021, Published online: 05 Dec 2021

References

  • Ahmadi, P. (2019). Environmental impacts and behavioral drivers of deep decarbonization for transportation through electric vehicles. Journal of Cleaner Production, 225, 1209–1219. https://doi.org/10.1016/j.jclepro.2019.03.334
  • Amini, M. H., Kargarian, A., & Karabasoglu, O. (2016). ARIMA-based decoupled time series forecasting of electric vehicle charging demand for stochastic power system operation. Electric Power Systems Research, 140, 378–390. https://doi.org/10.1016/j.epsr.2016.06.003
  • Bonsu, N. O. (2020). Towards a circular and low-carbon economy: Insights from the transitioning to electric vehicles and net zero economy. Journal of Cleaner Production, 256, 120659. https://doi.org/10.1016/j.jclepro.2020.120659
  • Chen, T. D., Kockelman, K. M., & Khan, M. (2013). Locating electric vehicle charging stations: Parking-based assignment method for Seattle, Washington. Transportation Research Record: Journal of the Transportation Research Board, 2385(1), 28–36. https://doi.org/10.3141/2385-04
  • Chen, T., & Guestrin, C. (2016). XGBoost: A scalable tree boosting system. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 785–794). San Francisco, CA. Association for Computing Machinery.
  • Chung, Y.-W., Khaki, B., Li, T., Chu, C., & Gadh, R. (2019). Ensemble machine learning-based algorithm for electric vehicle user behavior prediction. Applied Energy, 254, 113732. https://doi.org/10.1016/j.apenergy.2019.113732
  • Franke, T., Neumann, I., Bühler, F., Cocron, P., & Krems, J. F. (2012). Experiencing range in an electric vehicle: Understanding psychological barriers. Applied Psychology, 61(3), 368–391. https://doi.org/10.1111/j.1464-0597.2011.00474.x
  • Guo, F., Yang, J., & Lu, J. (2018). The battery charging station location problem: Impact of users’ range anxiety and distance convenience. Transportation Research Part E: Logistics and Transportation Review, 114, 1–18. 18. https://doi.org/10.1016/j.tre.2018.03.014
  • Hao, X., Wang, H., Lin, Z., & Ouyang, M. (2020). Seasonal effects on electric vehicle energy consumption and driving range: A case study on personal, taxi, and ridesharing vehicles. Journal of Cleaner Production, 249, 119403. https://doi.org/10.1016/j.jclepro.2019.119403
  • Jabeen, F., Olaru, D., Smith, B., Braunl, T., & Speidel, S. (2013). Electric vehicle battery charging behaviour: Findings from a driver survey. In Proceedings of the Australasian Transport Research Forum.
  • Khwaja, A. S., Venkatesh, B., & Anpalagan, A. (2020). Short-term individual electric vehicle charging behavior prediction using long short-term memory networks. In 2020 IEEE 25th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD).
  • Kim, S., Yang, D., Rasouli, S., & Timmermans, H. (2017). Heterogeneous hazard model of PEV users charging intervals: Analysis of four year charging transactions data. Transportation Research Part C: Emerging Technologies, 82, 248–260. https://doi.org/10.1016/j.trc.2017.06.022
  • Morrissey, P., Weldon, P., & O’Mahony, M. (2016). Future standard and fast charging infrastructure planning: An analysis of electric vehicle charging behaviour. Energy Policy, 89, 257–270. https://doi.org/10.1016/j.enpol.2015.12.001
  • Neubauer, J., & Wood, E. (2014). The impact of range anxiety and home, workplace, and public charging infrastructure on simulated battery electric vehicle lifetime utility. Journal of Power Sources, 257, 12–20. https://doi.org/10.1016/j.jpowsour.2014.01.075
  • Nilsson, M. (2011). Electric vehicles: The phenomenon of range anxiety. E. Consortium.
  • Oliver, E. (2010). Diversity in smartphone energy consumption. In Proceedings of the 2010 ACM Workshop on Wireless of the Students, by the Students, for the Students.
  • Shepero, M., & Munkhammar, J. (2018). Spatial Markov chain model for electric vehicle charging in cities using geographical information system (GIS) data. Applied Energy, 231, 1089–1099. https://doi.org/10.1016/j.apenergy.2018.09.175
  • Sun, X.-H., Yamamoto, T., & Morikawa, T. (2015). Charge timing choice behavior of battery electric vehicle users. Transportation Research Part D: Transport and Environment, 37, 97–107. https://doi.org/10.1016/j.trd.2015.04.007
  • Xu, M., Meng, Q., Liu, K., & Yamamoto, T. (2017). Joint charging mode and location choice model for battery electric vehicle users. Transportation Research Part B: Methodological, 103, 68–86. https://doi.org/10.1016/j.trb.2017.03.004
  • Xu, M., Yang, H., & Wang, S. (2020). Mitigate the range anxiety: Siting battery charging stations for electric vehicle drivers. Transportation Research Part C: Emerging Technologies, 114, 164–188. https://doi.org/10.1016/j.trc.2020.02.001
  • Yang, Y., Yao, E., Yang, Z., & Zhang, R. (2016). "Modeling the charging and route choice behavior of BEV drivers. Transportation Research Part C: Emerging Technologies, 65, 190–204. https://doi.org/10.1016/j.trc.2015.09.008
  • Yavasoglu, H., Tetik, Y., & Gokce, K. (2019). Implementation of machine learning based real time range estimation method without destination knowledge for BEVs. Energy, 172, 1179–1186. https://doi.org/10.1016/j.energy.2019.02.032
  • Yi, Z., Liu, X. C., Wei, R., Chen, X., & Dai, J. (2021). "Electric vehicle charging demand forecasting using deep learning model. Journal of Intelligent Transportation Systems, 1–14. https://doi.org/10.1080/15472450.2021.1966627

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.