Abstract

In order to enrich the judgment index of the lane departure and avoid a sensitive system which is caused by missing vehicle signals, a method of detecting fatigue lane departure based on human-vehicle-road characteristics has been proposed. At first, an experiment about fatigue lane departure has been taken. And then, relevant parameters that can reveal the human-vehicle-road characteristics are collected and analyzed, compared with that under normal lane changing. At last fatigue lane departure recognition model is constructed based on Gaussian Mixture-Hidden Markov Model (GM-HMM). The recognition results show good performance under online and offline tests.

Keywords:

Fatigue, fatigue lane departure, lane departure warning, LCA, recognition, warning system,

References

1. Ahmed, R., K.E.K. Emon and Md. F. Hossain, 2014. Robust driver fatigue recognition using image processing. Proceeding of the International Conference on Informatics, Electronics and Vision. Dhaka, May 23-24, pp: 1-6.
   CrossRef    
2. eSafety Forum, 2005. Digital maps working group. Final Report and Recommendations of the Implementation Road Map Working Group.
   
3. Haijing, H., 20013. Research on lane change intention recognition method for freeway driver. Ph.D. Thesis, School of Transportation Jilin University., Changchun.
   
4. Kuge, N., T., Yamamura, O. Shimoyama and A. Liu, 2000. A Driver Behavior Recognition Method Based on a Driver Model Framework. SAE Technical Paper, 2000-01-0349, pp: 47-54.
   
5. Lethaus, F. and J. Rataj, 2007. Do eye movements reflect driving manoeuvres? IET Intell. Transp. Sy., 1(3): 199-204.
   CrossRef    
6. Morris, B., A. Doshi and M. Trivedi, 2011. Lane change intent prediction for driver assistance: On-road design and evaluation. Proceeding of the IEEE Intelligent Vehicles Symposium (IV) Baden-Baden, Germany, pp: 895-901.
   Direct Link
7. Nakayama, O., T. Futami, T. Nakamura and E.R. Boer, 1999. Development of a Steering Entropy Method for Evaluating Driver Workload. SAE Technical Paper 1999-01-0892, SAE International Congress and Exposition. Detroit, Michigan, March. 1-4, pp: 1-12.
   Direct Link
8. Rogado, E., J.L. García, R. Barea, L.M. Bergasa and E. Lopez, 2009. Driver fatigue detection system. Proceeding of the IEEE International Conference on Robotics and Biomimetics. Bangkok, pp: 1105-1110.
   CrossRef    

Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.