TY - GEN
T1 - Decision-making model of overtaking behavior for automated driving on freeways
AU - Jianwei, Gong
AU - Xu, Youzhi
AU - Lu, Chao
AU - Guingming, Xiaog
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/8/19
Y1 - 2016/8/19
N2 - In this paper, we propose a decision-making model of overtaking behavior for automated driving on freeways. This model is composed of two main parts: a multilevel microscopic scene model and a Hierarchical State Machine (HSM). The multilevel microscopic scene model is used to describe the complex traffic situation, and in some specific situations, the automated vehicle will interact with other traffic participants to obtain additional information. On the other hand, the HSM focuses on the decision-making process, which consists of two stages: the emergence of overtaking intention based on the RBF neural network (RBFNN) and the judgment of overtaking condition based on the rules. The presented model has been integrated in our vehicle "Ray" and evaluated in the man-in-the-loop simulation environments built with Pre Scan and Matlab. Experimental results show that the proposed decision-making model is feasible and reliable.
AB - In this paper, we propose a decision-making model of overtaking behavior for automated driving on freeways. This model is composed of two main parts: a multilevel microscopic scene model and a Hierarchical State Machine (HSM). The multilevel microscopic scene model is used to describe the complex traffic situation, and in some specific situations, the automated vehicle will interact with other traffic participants to obtain additional information. On the other hand, the HSM focuses on the decision-making process, which consists of two stages: the emergence of overtaking intention based on the RBF neural network (RBFNN) and the judgment of overtaking condition based on the rules. The presented model has been integrated in our vehicle "Ray" and evaluated in the man-in-the-loop simulation environments built with Pre Scan and Matlab. Experimental results show that the proposed decision-making model is feasible and reliable.
UR - http://www.scopus.com/inward/record.url?scp=84988419064&partnerID=8YFLogxK
U2 - 10.1109/ICVES.2016.7548162
DO - 10.1109/ICVES.2016.7548162
M3 - Conference contribution
AN - SCOPUS:84988419064
T3 - Proceedings - 2016 IEEE International Conference on Vehicular Electronics and Safety, ICVES 2016
SP - 7
EP - 12
BT - Proceedings - 2016 IEEE International Conference on Vehicular Electronics and Safety, ICVES 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE International Conference on Vehicular Electronics and Safety, ICVES 2016
Y2 - 10 July 2016 through 12 July 2016
ER -