| dc.creator |
Naranjo, José E. |
|
| dc.creator |
González, Carlos |
|
| dc.creator |
García Rosa, Ricardo |
|
| dc.creator |
Pedro, Teresa de |
|
| dc.creator |
Haber Guerra, Rodolfo E. |
|
| dc.date |
2008-02-28T10:33:45Z |
|
| dc.date |
2008-02-28T10:33:45Z |
|
| dc.date |
2005-12 |
|
| dc.date.accessioned |
2017-01-31T01:00:29Z |
|
| dc.date.available |
2017-01-31T01:00:29Z |
|
| dc.identifier |
IEEE Transactions on Intelligent Transportation Systems, vol. 6, nº 4, Decembre 2005 |
|
| dc.identifier |
http://hdl.handle.net/10261/3106 |
|
| dc.identifier |
10.1109/TITS.2005.858622 |
|
| dc.identifier.uri |
http://dspace.mediu.edu.my:8181/xmlui/handle/10261/3106 |
|
| dc.description |
The Associate Editor for this paper was R. Goudy.
The authors are with the Industrial Computer Science Department, Instituto
de Automatica Industrial (CSIC), La Poveda-Arganda del Rey, 28500 Madrid. |
|
| dc.description |
The unmanned control of the steering wheel is, at present, one of the most important challenges facing researchers in autonomous vehicles within the field of intelligent transportation systems (ITSs). In this paper, we present a two-layer control
architecture for automatically moving the steering wheel of a mass-produced vehicle. The first layer is designed to calculate the
target position of the steering wheel at any time and is based on fuzzy logic. The second is a classic control layer that moves
the steering bar by means of an actuator to achieve the position targeted by the first layer. Real-time kinematic differential global positioning system (RTK-DGPS) equipment is the main sensor input for positioning. It is accurate to about 1 cm and can finely locate the vehicle trajectory. The developed systems are installed on a Citroen Berlingo van, which is used as a testbed vehicle. Once this control architecture has been implemented, installed, and tuned, the resulting steering maneuvering is very similar to
human driving, and the trajectory errors from the reference route are reduced to a minimum. The experimental results show that the combination of GPS and artificial-intelligence-based techniques behaves outstandingly. We can also draw other important conclusions regarding the design of a control system derived from human driving experience, providing an alternative mathematical formalism for computation, human reasoning, and integration of qualitative and quantitative information. |
|
| dc.description |
This work was supported in part by the Spanish Ministry of Education under Grant
ISAAC CICYT DPI2002-04064-C05-02, the Spanish Ministry of Public Works
under Grant COPOS BOE 280 November 22, 2002. Res. 22778, and the
Citroen Espana S.A. under Contract “Adquirir nuevos conocimientos sobre la introducción de las tecnologias de la información en el mundo del automóvil
y para difundirlos en los ambitos cientificos, empresariales y comerciales
(Autopia).” |
|
| dc.description |
Peer reviewed |
|
| dc.format |
631171 bytes |
|
| dc.format |
application/pdf |
|
| dc.language |
eng |
|
| dc.publisher |
Institute of Electrical and Electronics Engineers |
|
| dc.rights |
openAccess |
|
| dc.subject |
Architecture |
|
| dc.subject |
fuzzy control |
|
| dc.subject |
global positioning |
|
| dc.subject |
intelligent control |
|
| dc.subject |
road vehicle control |
|
| dc.title |
Power-Steering Control Architecture for Automatic Driving |
|
| dc.type |
Artículo |
|