@Article{2018.100000030,
AUTHOR = {Ling Wu, Haoxue Liu, Tong Zhu, Yueqi Hu},
TITLE = {NARX Network Based Driver Behavior Analysis and Prediction Using Time-series Modeling},
JOURNAL = {Intelligent Automation \& Soft Computing},
VOLUME = {24},
YEAR = {2018},
NUMBER = {3},
PAGES = {633--642},
URL = {http://www.techscience.com/iasc/v24n3/39788},
ISSN = {2326-005X},
ABSTRACT = {The objective of the current study was to examine how experienced and 
inexperienced driver behaviour changed (including heart rate and longitudinal 
speeds) when approaching and exiting highway tunnels. Simultaneously, the 
NARX neural network was used to predict real-time speed with the heart rate 
regarded as the input variable. The results indicated that familiarity with the 
experimental route did decrease drivers’ mental stress but resulted in higher 
speed. The proposed NARX model could predict synchronous speed with high 
accuracy. These results of the present study concern how to establish the 
automated driver model in the simulation environment.},
DOI = {10.31209/2018.100000030}
}