TY - GEN
T1 - Adaptive driver assistance system based on Traffic Information Saliency Map
AU - Kim, Jihun
AU - Kim, Seonggyu
AU - Mallipeddi, Rammohan
AU - Jang, Giljin
AU - Lee, Minho
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/10/31
Y1 - 2016/10/31
N2 - In this paper, we propose a framework that can prevent accidents due to careless or inattentive driving by providing the necessary traffic information to the driver. The proposed system complements the driver by providing the missed cognitive information regarding the traffic. The proposed system is divided into three parts. First, the system checks the condition of the driver in real time, and detects the status of the driver in terms of driving ability. Second, we propose bottom-up and top-down processes based on Traffic Information Saliency Map (TISM) which contains the distribution corresponding to the external road information using bottom-up traffic information saliency map and top-down importance information such as pedestrian and traffic light detection results. Computer experimental results show that the proposed method works well for monitoring of internal situation for driver's attention as well as external environment.
AB - In this paper, we propose a framework that can prevent accidents due to careless or inattentive driving by providing the necessary traffic information to the driver. The proposed system complements the driver by providing the missed cognitive information regarding the traffic. The proposed system is divided into three parts. First, the system checks the condition of the driver in real time, and detects the status of the driver in terms of driving ability. Second, we propose bottom-up and top-down processes based on Traffic Information Saliency Map (TISM) which contains the distribution corresponding to the external road information using bottom-up traffic information saliency map and top-down importance information such as pedestrian and traffic light detection results. Computer experimental results show that the proposed method works well for monitoring of internal situation for driver's attention as well as external environment.
KW - Advanced driver assistance system
KW - Gaze detection
KW - Saliency map
KW - Traffic light recognition
UR - http://www.scopus.com/inward/record.url?scp=85007190410&partnerID=8YFLogxK
U2 - 10.1109/IJCNN.2016.7727434
DO - 10.1109/IJCNN.2016.7727434
M3 - Conference contribution
AN - SCOPUS:85007190410
T3 - Proceedings of the International Joint Conference on Neural Networks
SP - 1918
EP - 1923
BT - 2016 International Joint Conference on Neural Networks, IJCNN 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 International Joint Conference on Neural Networks, IJCNN 2016
Y2 - 24 July 2016 through 29 July 2016
ER -