A fuzzy control based self-optimizing PID model for autonomous car following on highway

Wang, Q.; Xu, S.; Xu, Honglei

doi:10.1109/WCSN.2014.87

228397.pdf (210.7Kb)

Access Status

Open access

Authors

Wang, Q.

Xu, S.

Xu, Honglei

Date

2015

Type

Conference Paper

Metadata

Show full item record

Citation

Wang, Q. and Xu, S. and Xu, H. 2015. A Fuzzy Control Based Self-Optimizing PID Model for Autonomous Car Following on Highway, in Proceedings of the 2014 International Conference on Wireless Communication and Sensor Network (WCSN 2014), Dec 13-14 2014, pp. 395-399. Wuhan, China: Institute of Electrical and Electronics Engineers.

Source Title

Proceedings - 2014 International Conference on Wireless Communication and Sensor Network, WCSN 2014

Source Conference

2014 International Conference on Wireless Communication and Sensor Network, WCSN 2014

DOI

10.1109/WCSN.2014.87

ISBN

9781479970919

School

Department of Mathematics and Statistics

Remarks

Copyright © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

URI

http://hdl.handle.net/20.500.11937/59397

Collection

Curtin Research Publications

Abstract

Controlling real-time distances between vehicles is extremely significant for keeping safe driving on highway. At the same time, status of traffic stream, whole time delay and errors in controlling also have impacts on the control at a high driving speed. In this paper, a self-optimizing PID model based on fuzzy control is proposed for assisting a car to follow another one at a safe distance. The proposed model is established on a wireless sensor network sharing information for perceiving different status of traffic stream. In the designed experiment, the fuzzy PID controller is able to adapt nonlinear and time-varying features of behaviors in traffic stream. Comparing with general PID controllers, the fuzzy PID controller has a better performance on dynamic behaviors. According to comparison with the effects of controlling in different conditions, simulation results show that the proposed model is able to adjust and control the follower's behaviors in different situations on highway.