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Drag coefficient modeling of heterogeneous connected platooning vehicles via BP neural network and PSO algorithm

  • Published:2021-10 Issue: Volume: Page:
  • ISSN:0925-2312
  • Container-title:Neurocomputing
  • language:en
  • Short-container-title:Neurocomputing

Author:

Luo Qianyue,Li Jiaxing,Zhang Hui

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference45 articles.

1. Effect of the frontal edge radius in a platoon of bluff bodies;Gheyssens;SAE Int. J. Commercial Veh.,2016

2. Fuel-efficient en route speed planning and tracking control of truck platoons;Guo;IEEE Trans. Intell. Transp. Syst.,2019

3. Heavy-duty vehicle platoon formation for fuel efficiency;Liang;IEEE Trans. Intell. Transp. Syst.,2016

4. An experimental study on the fuel reduction potential of heavy duty vehicle platooning;Alam,2010

5. Experimental validation of connected automated vehicle design among human-driven vehicles;Ge;Transp. Res. Part C: Emerging Technol.,2018

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4. Dynamic Tracking Method for Train Number of Rail Transit Signal System;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2024

5. Review on aerodynamic characteristics and energy recovery of vehicle platoon;Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering;2023-12-15
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