Grey models for short-term queue length predictions for adaptive traffic signal control
作者：
Highlights：
• Six Grey System theory models for queue length prediction studied at traffic arterials.
• The Grey Cosine models demonstrated better accuracy than other compared models.
• The Cosine model with Fourier error correction demonstrates the best accuracy.
• Grey models do not require a large amount of data or computational time.
• Grey models are compared to machine learning methods.
摘要
•Six Grey System theory models for queue length prediction studied at traffic arterials.•The Grey Cosine models demonstrated better accuracy than other compared models.•The Cosine model with Fourier error correction demonstrates the best accuracy.•Grey models do not require a large amount of data or computational time.•Grey models are compared to machine learning methods.
论文关键词：Grey systems,Time series,Long short-term memory neural network,Queue length prediction,Machine learning
论文评审过程：Received 28 December 2019, Revised 8 July 2021, Accepted 13 July 2021, Available online 24 July 2021, Version of Record 28 July 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.115618
