Steering control algorithm for intelligent vehicle based on support vector machine

被引：0

作者：

Zhu, Yuan ^{[1
]}

Xu, Xinxi ^{[2
]}

Xu, Youchun ^{[3
]}

Wang, Xiao ^{[3
]}

机构：

[1] Institute of Medical Equipment, Academy of Military Medical Sciences, Department of Automobile Engineering, Academy of Military Transportation, Tianjin

[2] Institute of Medical Equipment, Academy of Military Medical Sciences

[3] Department of Automobile Engineering, Academy of Military Transportation

来源：

Journal of Convergence Information Technology | 2012年 / 7卷 / 22期

关键词：

Intelligent vehicle; Steering control algorithm; Support victor machine;

D O I：

10.4156/jcit.vol7.issue22.70

中图分类号：

学科分类号：

摘要：

The traditional steering control method is to get the model of vehicle through strict derivation and using LQ or PID algorithms et al. to design the controller for the vehicle. These algorithms require accurately dynamic and mechanic model which are very difficult. Aiming at the intelligent vehicle model, a vision-based support vector machine (SVM) steering control algorithm is brought forward. According to the characteristics of intelligent vehicle, the SVM control model is designed. With the input of white-line position value of a road map, the algorithm outputs the steering angle of the steering wheels. 153 groups of image data are trained by SVM, which contain 17 groups of linear state models as well as 136 groups of turning state model. The test indicates that the algorithm can learn the control tactic of the operator very well, and has better stability and robustness.

引用

页码：593 / 599

页数：6

共 20 条

[1]

Do K.D., Jiang Z.P., Pan J., Nijmeijer H., A global output-feed-back controller for stabilization and tracking of under actuated O-DN, A spherical underwater vehicle, Automatica, 40, 1, pp. 117-120, (2004)

[2]

Lauffenburger J.P., Basset M., Coffin F., Et al., Driver-aid system using path-p lanning for lateral vehicle control, Control Engineering Practice, 11, 2, pp. 217-231, (2003)

[3]

Martinet P., Thibaud C., Automatic guided vehicles: Robust controller design in image space, Autonomous Robots, 8, 1, pp. 25-42, (2000)

[4]

Marinoa R., Scalzia S., Netto M., Nested PID steeringcontrol for lane keeping in autonomous vehicles, Control Engineering Practice, 19, 12, pp. 1459-1467, (2011)

[5]

Rokonuzzaman M., Ferdous S.M., Ovy E.G., Hoque M.A., Smooth track-keeping and real time obstacle detection algorithm and its PID controller implementation for an automated wheeled line following robot, Advanced Materials Research, 201-203, pp. 1966-1971, (2011)

[6]

Marino R., Scalzi S., Netto M., Nested PID steering control for lane keeping in autonomous vehicles, Control Engineering Practice, 19, 12, pp. 1459-1467, (2011)

[7]

Scalzi S., Orlando G., Netto M., A nested PID steering control for lane keeping in vision based autonomous vehicles, pp. 2885-2890, (2009)

[8]

Asami M., Sadayuki T., Look-Ahead-Distance for Lateral Control of Vision-Based Vehicles, pp. 205-215, (2010)

[9]

Sentouh C., Popieul J.C., Debernard S., Fuzzy Takagi-Sugeno LQ controller for a shared control of vehicle, pp. 956-961, (2011)

[10]

Ok L.Y., Youngseop S., Choo C.C., Multirate active steering control for autonomous vehicle lateral maneuvering, pp. 772-777, (2012)

← 1 2 →