The Simulation System Of Individual Travel Behavior Based On Swarm

Urban transportation is a typical complex adaptive system. Traffic congestion has become a big stumbling block of urban economic development as urban land and population expand. Traffic jams lies in that there is a gap between traffic demand and supply, the study of traffic demand must be done to solve the traffic problems. The study of indevidual's travel behavior is the basement of traffic demand management research, seeing from the CAS (complex adaptive system) viewpoint, to study how the individual travel behaviors become the social travel phenomenon is very important.The dissertation is based on the CAS theory, adopts the multi-agent modeling method, practices on the Swarm platform, and simulates the travel behavior. The dissertation certres on the following aspects:Firstly, the dissertation summarizes the current achievements and tendency on travel behavior and complex adaptive system modeling in domestics and abroad. Subsequently, the concepts and methods of complex adaptive system theory are presented.Secondly, from the complex adaptive system viewpoint, the dissertation analyzes the individual travel behavior, develops the relevant model, and realizes the simulation system via programming in Java.Lastly, the dissertation changes the behavior of individual's co-action, through the observing of the contrast experiments'outputs, researches the emergence phenomenon from simple to complex in individual travel behavior, and gets the conclusions as follows: (1) The positive effect of group learning exists in the travel system, the effect of group learning is better than that of individual learning. (2) Within a certain limit, the communication of travel experience can improve the whole travel situation, but more information communication become invalid, even brings adverse effect in excess of that limit. When the road network is overloaded, the adverse effect is even more obvious so as to cause the congestion vibration and congestion shift.