TY - GEN
T1 - Prediction of Following Vehicle Trajectory Considering Operation Characteristics of a Human Driver
AU - Woo, Hanwool
AU - Madokoro, Hirokazu
AU - Sato, Kazuhito
AU - Tamura, Yusuke
AU - Yamashita, Atsushi
AU - Asama, Hajime
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/1
Y1 - 2020/1
N2 - In this paper, we propose a novel method to predict the trajectory of a following vehicle, based on the operation characteristics of a driver. If a lead vehicle suddenly decelerates to avoid colliding with interrupting vehicles, it may lead to an accident with the following vehicle. To prevent such accidents, it would be beneficial to predict the future positions of surrounding vehicles. Previous studies have proposed similar prediction methods; however, these studies have not considered the operation characteristics of drivers, even though the prediction performance largely depends on these characteristics. In this research, we assumed a driving scene wherein a human driver follows an autonomous vehicle. The proposed method is implemented in the autonomous vehicle. Consequently, the method is able to predict the trajectory of the following vehicle operated by a human driver. The contribution of this paper is to estimate the operation characteristics of the following driver and to apply the estimated result to obtain the trajectory prediction. It is demonstrated that the proposed method shows high prediction accuracy as compared to the previous methods.
AB - In this paper, we propose a novel method to predict the trajectory of a following vehicle, based on the operation characteristics of a driver. If a lead vehicle suddenly decelerates to avoid colliding with interrupting vehicles, it may lead to an accident with the following vehicle. To prevent such accidents, it would be beneficial to predict the future positions of surrounding vehicles. Previous studies have proposed similar prediction methods; however, these studies have not considered the operation characteristics of drivers, even though the prediction performance largely depends on these characteristics. In this research, we assumed a driving scene wherein a human driver follows an autonomous vehicle. The proposed method is implemented in the autonomous vehicle. Consequently, the method is able to predict the trajectory of the following vehicle operated by a human driver. The contribution of this paper is to estimate the operation characteristics of the following driver and to apply the estimated result to obtain the trajectory prediction. It is demonstrated that the proposed method shows high prediction accuracy as compared to the previous methods.
UR - http://www.scopus.com/inward/record.url?scp=85082612222&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85082612222&partnerID=8YFLogxK
U2 - 10.1109/SII46433.2020.9026243
DO - 10.1109/SII46433.2020.9026243
M3 - Conference contribution
AN - SCOPUS:85082612222
T3 - Proceedings of the 2020 IEEE/SICE International Symposium on System Integration, SII 2020
SP - 712
EP - 717
BT - Proceedings of the 2020 IEEE/SICE International Symposium on System Integration, SII 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE/SICE International Symposium on System Integration, SII 2020
Y2 - 12 January 2020 through 15 January 2020
ER -