TY - GEN
T1 - Evaluation of the autonomous parking system based on bp neural network
AU - Du, Fangjing
AU - Zhao, Yanan
AU - Gao, Li
AU - Wang, Wenhao
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/9/20
Y1 - 2017/9/20
N2 - The autonomous parking system is an intelligent system which can park a car into a parking spot. Recently, more and more studies pay attention on this system. However, research on evaluation of autonomous parking system in these studies is not enough. Because most of evaluation methods of intelligent vehicle system are based on task completion degree, the evaluation of autonomous parking system cannot show its real intelligent level. In order to ensure the feasibility and accuracy of evaluation of autonomous parking system, the paper proposes an effective evaluation method based on BP neural network. The evaluation method is established based on autonomous parking system evaluation index system, using BP neural network evaluation model. Using samples collected from the autonomous parking system in intelligent vehicles, the model is trained by MATLAB software and the evaluation model is tested by samples. The result shows that the simulation values are very close to the expected ones, which means the feasibility and accuracy of the evaluation model.
AB - The autonomous parking system is an intelligent system which can park a car into a parking spot. Recently, more and more studies pay attention on this system. However, research on evaluation of autonomous parking system in these studies is not enough. Because most of evaluation methods of intelligent vehicle system are based on task completion degree, the evaluation of autonomous parking system cannot show its real intelligent level. In order to ensure the feasibility and accuracy of evaluation of autonomous parking system, the paper proposes an effective evaluation method based on BP neural network. The evaluation method is established based on autonomous parking system evaluation index system, using BP neural network evaluation model. Using samples collected from the autonomous parking system in intelligent vehicles, the model is trained by MATLAB software and the evaluation model is tested by samples. The result shows that the simulation values are very close to the expected ones, which means the feasibility and accuracy of the evaluation model.
KW - Autonomous parking system
KW - BP neural network
KW - Evaluation
UR - http://www.scopus.com/inward/record.url?scp=85034415651&partnerID=8YFLogxK
U2 - 10.1109/IHMSC.2017.185
DO - 10.1109/IHMSC.2017.185
M3 - Conference contribution
AN - SCOPUS:85034415651
T3 - Proceedings - 9th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2017
SP - 324
EP - 327
BT - Proceedings - 9th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2017
Y2 - 26 August 2017 through 27 August 2017
ER -
