An innovative method to measure and predict drivers’ behaviour in highway extra-long tunnels using time-series modelling-Reference-Cited by-同舟云学术

An innovative method to measure and predict drivers’ behaviour in highway extra-long tunnels using time-series modelling

Published:2020-01-09 Issue:1 Volume:38 Page:207-217
ISSN:1064-1246
Container-title:Journal of Intelligent & Fuzzy Systems
language:
Short-container-title:IFS

Author:

Wu Ling¹,Hu Hao¹,Zhao Weihua¹,Liu Haoxue²,Zhu Tong²

Affiliation:

1. School of Vehicle Engineering, Xi’an Aeronautical University, Xi’an, China

2. Key Laboratory for Automotive Transportation Safety Enhancement Technology of the Ministry of Communication, Chang’an University, Xi’an, China

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference25 articles.

1. Study of rules of traffic accidents in expressway tunnels [J];Lai;Tunnel Construction,2017

2. An empirical study of the effects of road tunnel on driving performance[J];Calvi;Procedia-Social and Behavioral Sciences,2012

3. Influence of the lighting system on the driver’s behavior in road tunnels: A driving simulator study[J];Domenichini;Journal of Transportation Safety & Security,2016

4. Distribution characteristics and countermeasures of traffic accidents in expressway tunnel group[J];Zhang;Journal of Chang’an University: Natural Science Edition,2007

5. Bayesian prediction of traffic accident based on vehicle speed[J];Lin;Chinese Journal of Safety Science,2003

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Comparative study on drivers’ eye movement characteristics and psycho-physiological reactions at tunnel entrances in plain and high-altitude areas: A pilot study;Tunnelling and Underground Space Technology;2022-04