| Full text | |
| Author(s): |
Assuncao, Arthur N.
[1, 2]
;
Aquino, Andre L. L.
[3]
;
Santos, Ricardo C. Camara de M.
[1]
;
Guimaraes, Rodolfo L. M.
[1]
;
Oliveira, Ricardo A. R.
[1]
Total Authors: 5
|
| Affiliation: | [1] Univ Fed Ouro Preto, Dept Comp, BR-35400000 Ouro Preto, MG - Brazil
[2] Inst Fed Educ Ciencia & Tecnol Sudeste Minas Gera, BR-36240000 Santos Dumont, MG - Brazil
[3] Univ Fed Alagoas, Inst Comp, BR-57072970 Maceio, AL - Brazil
Total Affiliations: 3
|
| Document type: | Journal article |
| Source: | SENSORS; v. 19, n. 14 JUL 12 2019. |
| Web of Science Citations: | 0 |
| Abstract | |
This paper proposes the use of the Statistical Process Control (SPC), more specifically, the Exponentially Weighted Moving Average method, for the monitoring of drivers using approaches based on the vehicle and the driver's behavior. Based on the SPC, we propose a method for the lane departure detection; a method for detecting sudden driver movements; and a method combined with computer vision to detect driver fatigue. All methods consider information from sensors scattered by the vehicle. The results showed the efficiency of the methods in the identification and detection of unwanted driver actions, such as sudden movements, lane departure, and driver fatigue. Lane departure detection obtained results of up to 76.92% (without constant speed) and 84.16% (speed maintained at approximate to 60). Furthermore, sudden movements detection obtained results of up to 91.66% (steering wheel) and 94.44% (brake). The driver fatigue has been detected in up to 94.46% situations. (AU) | |
| FAPESP's process: | 15/24544-5 - Data sampling in wireless sensor networks: integrating applications through the internet |
| Grantee: | André Luiz Lins de Aquino |
| Support Opportunities: | Regular Research Grants |