| Automated Highway System (AHS) is the most difficulty sub system in Intelligent Transport System(ITS). The system includes vehicle automatic navigation and control, traffic management automation and traffic accident treatment automation. It is the final goal for ITS, i.e. integration of human, vehicle and road. Lane keeping system is one of the key technologies of AHS in which vehicle can be run following the anticipant lane automatically based upon the navigation installation and vehicle- mounted sensors. Vision navigation and magnetic information navigation are two types of automatic driving. Vision navigation is easy to disturbed by weather and road condition, however magnetic marker navigation hasn't these disadvantages. Its safety and reliability can be enhanced if these two types are used in one system. This is why magnetic marker navigation becomes a hotspot in recent years internationally. In China, vision navigation is the main research project for automatic driving, however only our group has studied magnetic marker navigation in lane keeping system, no any other reports have been searched.This dissertation outlines the study on several problems of vehicle lane keeping system based on magnetic markers. Site experiment were carried out on the testing vehicle for AHS and the magnetic markers road in National Intelligent Transport System Center. Also, study on multi-sensor information fusion and control model by using neural net system, fuzzy logic and genetic algorithm were carried out. The work completed are as follows mainly:(1) Hardware system for lane keeping system including magnetic marker, magnetic sensor, control system and executor machine were designed. Research progress of magnetic sensor is described in detail. Test result indicated that the self-designed magnetic marker can be used to obtained magnetic information.(2) Having analyzed the information fusion technology, threemathematical models were made based on the signal sources obtained from self-designed magnetic sensor. The neural net method is discussed in detail, the configuration of neural net is established, study algorithm is decided. Training data were obtained from experiment. Simulation indicated that neural net method is more accurate than'the others two methods. In fact, information fusion modal is the location of vehicle lateral position which establishes research fundament of control modal later.(3) The fuzzy controller based on magnetic markers is designed. The changeable area and hierarchical genetic algorithm is studied; several examples indicated that this algorithm which can be used to search parameter of fuzzy controller is effective. Site experiment showed that designed fuzzy controller can be used in lane keeping system.(4) The significant of magnetic marker coding system is approachedtheoretically, structure of this coding system is introduced; this coding systemis designed according to test requirement.(5)Based on fuzzy control theory, fuzzy neural network (FNN) controlleris introduced; the changeable area and hierarchical genetic algorithm is usedto training fuzzy neural network. Simulation indicated that this designedfuzzy neural controller is effective.(6) Based on the discussion on learning control method, control model learning in AHS, particular in the important and necessity of online learning, is analyzed. Structure model of online learning control for lane keeping system is designed. It provides the theoretical fundament for further study on online learning control in the future.
|
PDF Full Text Request