Volume 4, Issue 3, May 2011, Pages 386 - 393
Driver Intention Recognition Method Using Continuous Hidden Markov Model
- Haijing Hou, Lisheng Jin, Qingning Niu, Yuqin Sun, Meng Lu
- Corresponding Author
- Haijing Hou
Available Online 1 May 2011.
- https://doi.org/10.2991/ijcis.2011.4.3.13How to use a DOI?
- In order to make Intelligent Transportation System (ITS) work effectively, a driver intention recognition method is proposed. In this research, three different recognition models were developed based on Continuous Hidden Markov Model (CHMM), and could distinguish left and right lane change intention from normal lane keeping intention. Subjects performed lane change maneuvers and lane keeping maneuvers with driving simulator which simulated highway scenes, parameters that highly correlated with lane change behavior were collected and analyzed. A series of testings and comparisons were done to obtain the optimal model structure and feature set. Results show that, taking the steering wheel angel, steering wheel angle velocity and lateral acceleration as the optimal observation signals, the accuracy can achieve up 95%, and it proved very effective in terms of early intention recognition.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - JOUR AU - Haijing Hou AU - Lisheng Jin AU - Qingning Niu AU - Yuqin Sun AU - Meng Lu PY - 2011 DA - 2011/05 TI - Driver Intention Recognition Method Using Continuous Hidden Markov Model JO - International Journal of Computational Intelligence Systems SP - 386 EP - 393 VL - 4 IS - 3 SN - 1875-6883 UR - https://doi.org/10.2991/ijcis.2011.4.3.13 DO - https://doi.org/10.2991/ijcis.2011.4.3.13 ID - Hou2011 ER -