To reduce the risk of lane changes, a method for lane changing intent identification is proposed based on the logistic model. By using faceLAB visual tracking system, experiments were conducted under real road environment for the purpose of studying drivers' lane changing intent identification. On the basis of the drivers' fixation characteristics of the rearview mirrors before lane changing operation, the size of the time window for lane changing behavior is determined. Based on difference analysis of visual characteristics between lane keeping and lane changing intent stages, saccade numbers, visual search width in the horizontal direction, saccade amplitude, and standard deviation of head rotation angles in the horizontal direction are selected as the characteristic indice to identify drivers' lane changing intent. The logistic model is constructed based on the leaning samples'characteristics. The model is applied to the lane changing intent identification process after the validity test. The results show that the identification rate reached 90.24%. Compared with the lane changing intent identification based on turn signals, the logistic model has significant advantages in terms of time series and identification rate.
PENG Jinshuan
,
FU Rui
,
SHAO Yiming
,
XU Lei
. Lane Changing Intent Identification Based on Logistic Regression Model[J]. Science & Technology Review, 2014
, 32(14)
: 69
-73
.
DOI: 10.3981/j.issn.1000-7857.2014.14.011
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