A hierarchical prediction model for lane-changes based on combination of fuzzy C-means and adaptive neural network

作者：

Highlights：

• A hierarchical prediction model is proposed to predict steering angles.

• The model combines fuzzy c-means and adaptive neural network.

• A clustering learning method is adopted to optimize parameters of sub neural network.

• Experiments are conducted in the driving simulator under different scenarios.

• Prediction results show the model can achieve high performance.

摘要

•A hierarchical prediction model is proposed to predict steering angles.•The model combines fuzzy c-means and adaptive neural network.•A clustering learning method is adopted to optimize parameters of sub neural network.•Experiments are conducted in the driving simulator under different scenarios.•Prediction results show the model can achieve high performance.

论文关键词：Lane changes,Fuzzy C-means algorithm,Neural network,Driving simulation,Driving prediction

论文评审过程：Received 24 April 2018, Revised 3 March 2019, Accepted 16 April 2019, Available online 17 April 2019, Version of Record 25 April 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.04.032