Construction Of Signal Intersections Multiple Domain Integrated Model And Its Application

Urban traffic system is a complex giant system; most of th’e systems elements aredynamic and the relationship between the elements is complicated. Moreover, the urbantraiffc system consists of complex multi-knowledge, which involves many diffeerntfields. To research and simulate a complex system comprehensively，choosing aneiffcient way of knowledge modeling and a tool of system simulation is necessary.Ontology is a good knowledge carirer and it can establish a link between the real worldand computer information system rfom the semantic and knowledge level; and thecellular automata model as a simulation tool of a complex system, has been widely usedin natural science and social science. Therefore, this paper chooses ontology as theguiding ideology of building the model，and the cellular automata as a model tool forsimulation. Based on the support of National Natural Science Foundation Project, andtake the signal intersection as the example background, this paper research the complexsystem’s modeling problem, which integrated multi-domain heterogeneous knowledge.The research point includes the method and the application of integrated modeling andmapping rules. The main work as follows:(1)Proposes a multiple majors domain ontology modeling method. Throughmulti-level analyzing the traiffc system，extracts the hierarchical feature according thetraiffc characteristics. Using the ontology as guidance, build the multi-level traiffcengineeirng ontology model，traiffc behavior ontology model and the other domain oftraffic system’s ontology model. Owing to the h’umans core influence in the trafficbehavior system, the complexity and dynamic attirbution, this paper takes the theory ofplanned behavior as the behavior model’s architecture.(2)The integration of the traiffc engineering model and the traiffc behavior model.This paper integrates the two different domain models through hierarchical integrationmethod，and expanse the model rfom the core elements human. It resolves the problemof rich the integrated model.(3)Designs and apply the mapping rules between the multiple majors domainontology model and cellular automata physical model. Through the mapping rules, theontology model is mapped to the cellular automata model. It is a key point to construct adynamic model of complex system. Based on the multiple domain of the ontologymodel and the composition of the cellular automata model, groups the mapping rules and defines it as the meta-rules. It is the mapping method in this paper.(4) Gives the instance scene to validate the construction model method. Throughmodifying the scene demand in the ontology model, it maps the cellular automata modeland then analysis the index rfom the simulation results and validate the moders rational.The proposed modeling method based on the multi level analysis provides a newidea to the ontology modeling of the complex system. In addition，the mapping betweenthe two models has practical signiifcance to realize the ontology model automatically,and also provides a reference for the exploration of th’e complex systems automaticmodeling.