  To improve driving safety and avoid car accidents, Advanced Driver Assistance
Systems (ADAS) are given significant attention. Recent studies have focused on
predicting driver intention as a key part of these systems. In this study, we
proposed new framework in which 4 inputs are employed to anticipate diver
maneuver using Brain4Cars dataset and the maneuver prediction is achieved from
5, 4, 3, 2, 1 seconds before the actual action occurs. We evaluated our
framework in three scenarios: using only 1) inside view 2) outside view and 3)
both inside and outside view. We divided the dataset into training, validation
and test sets, also K-fold cross validation is utilized. Compared with
state-of-the-art studies, our architecture is faster and achieved higher
performance in second and third scenario. Accuracy, precision, recall and
f1-score as evaluation metrics were utilized and the result of 82.41%, 82.28%,
82,42% and 82.24% for outside view and 98.90%, 98.96%, 98.90% and 98.88% for
both inside and outside view were gained, respectively.
