Please use this identifier to cite or link to this item:
|標題:||Autonomous Vehicle Parking Using Hybrid Artificial Intelligent Approach||作者:||Lee, C.K.
|關鍵字:||Optimization;Vehicle parking;Genetic algorithm;Petri net;Fuzzy;control;mobile robot;genetic algorithms;neural-network;fuzzy;car||Project:||Journal of Intelligent & Robotic Systems||期刊/報告no：:||Journal of Intelligent & Robotic Systems, Volume 56, Issue 3, Page(s) 319-343.||摘要:||
This paper devotes to design and implement a hybrid artificial intelligent control scheme for a car-like vehicle to perform the task of optimal parking. The parallel parking control scheme addresses three issues: trajectory planner, decisional kernel, and trajectory tracking control. Design of the control scheme consists of several techniques: genetic algorithm, Petri net, and fuzzy logic control. The genetic algorithm is used to determine the feasible parking locations. The Petri net is used to replace the traditional decision flow chart and plan alternative parking routes especially in global space. The parking routine can be re-performed if the initially assigned route is interfered or when the targeted parking space has been occupied. The fuzzy logic controller is used to drive the vehicle along with the optimal parking route. The proposed scheme is put into several scenarios to test and verify its applicability and to manifest its distinguished features.
|Appears in Collections:||電機工程學系所|
Show full item record
TAIR Related Article
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.