DocumentCode
3241665
Title
Artificial neural network for predictions of vehicle drivable range and period
Author
Chen, Yuan-Lin ; Chih Hsien Huang ; Kuo, Yao-Wen ; Wang, Shung-Sung
Author_Institution
Inst. of Electro-Mech. Eng., Ming Chi Univ. of Technol., New Taipei, Taiwan
fYear
2012
fDate
24-27 July 2012
Firstpage
329
Lastpage
333
Abstract
An artificial neural network for predicting the drivable range and period for vehicles under remaining fuel is presented in this paper. The driver´s driving behaviors, vehicle condition and traffic route are all taking into consideration. The presented method could learn from the statuses of vehicle such as vehicle speed and engine speed and traffic route to make a prediction of vehicle drivable range and period under remaining fuel. The experimental results are presented for to guarantee the artificial neural network could estimate the vehicle drivable range and period accurately.
Keywords
neural nets; road traffic; traffic engineering computing; artificial neural network; driving behaviors; engine speed; remaining fuel; traffic route; vehicle condition; vehicle drivable range; vehicle speed; Artificial neural networks; Engines; Estimation; Fuels; Neurons; Training; Vehicles; artificial neural network; driver´s driving behaviors; vehicle drivable period; vehicle drivable range;
fLanguage
English
Publisher
ieee
Conference_Titel
Vehicular Electronics and Safety (ICVES), 2012 IEEE International Conference on
Conference_Location
Istanbul
Print_ISBN
978-1-4673-0992-9
Type
conf
DOI
10.1109/ICVES.2012.6294324
Filename
6294324
Link To Document