Pemodelan Dinamika Kendaraan dengan Jaringan Syaraf Tiruan
DOI:
https://doi.org/10.21512/comtech.v5i1.2588Keywords:
autonomous vehicle, artificial neural networks, feedforward neural networks, back propagation methodAbstract
Creating autonomous vehicle that can drive without a driver is a dream of the researchers who see the application of such a system will be needed in the future. Realizing such a system requires a dynamic model of the vehicle. It may be obtained by analytical method using dynamic equations. However, this way is rather difficult to do, especially in modeling the non-linear factors caused by tires, suspension, road conditions, etc. This study, in order to avoid difficulties in the analytical method, used artificial neural networks to model the dynamic system of the autonomous vehicle. It utilized data input from the camera sensor and vehicle speed.Plum Analytics
References
Ghazizadeh, A., Fahim, M., & El-Gindy. (1996). Neural networks representation of a vehicle model: Neuro-vehicle (NV). Int. J. Veh. Design, 17(1), 55-75.
Mathworks. (n.d.). Modeling a Vehicle Dynamics System. Diakses dari http://www.mathworks.com/help/ident/examples/modeling-a-vehicle-dynamics-system.html
Qiang, L., Huiyi, W., & Konghui, G. (1999, Sept.). Identification and control of fourwheel-steering vehicles based on neural network. Vehicle Electronics Conf., 1, 250-253.
Rivals, I., Canas, D., Personnaz, L., & Dreyfus, G. (1994). Modeling and control of mobile robots and intelligent vehicles by neural networks. IEEE Intelligent Vehicle Symp, June 1994, 137-142.
Yim, Y. U., & Oh, Se-Young. (2004, Jul.). Modeling of Vehicle Dynamics From Real Vehicle Measurements Using a Neural Network With Two-Stage Hybrid Learning for Accurate Long-Term Prediction. IEEE Transactions on Vehicular Technology, 53(4), 1076-1084.
Downloads
Published
Issue
Section
License
Authors who publish with this journal agree to the following terms:
a. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License - Share Alike that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
b. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
c. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
USER RIGHTS
All articles published Open Access will be immediately and permanently free for everyone to read and download. We are continuously working with our author communities to select the best choice of license options, currently being defined for this journal as follows: