Evolutionary Dynamics Of Urban Travel In Complex Networks

Transportation system is a comprehensive,dynamic and open complex system.Its dynamic characteristics mainly reflect the evolution of the self-organizing interaction among intelligent individuals in the system with the changes of time and space.As a typical representative of traffic interaction,the complexity and importance of group travel behavior are increasing with the acceleration of urbanization.Reasonable coordination of group travel behavior can effectively improve the overall efficiency of the transportation system.In recent years,complex network is new system theory,which has great advantages in the study of individual microscopic interaction and system macroscopic evolution.Therefore,based on this theory,this paper describes the interactive characteristics of traffic travel behavior and systematically analyzes its dynamic evolution mechanism.The specific research contents are as follows:Firstly,a travel network model is constructed to analyze the structural characteristics of travel activities.The Mean Shift algorithm is used to cluster the Geolife trajectory data of Microsoft research.The traffic zones are regarded as the network node,and the connections on the travel chains are used to build the links of network.Based on Space P method,the travel network model is constructed.The statistical characteristics of the network structure show that the network model has good applicability and accords with the statistical characteristics in reality.Meanwhile,through the nodes attacking and edges attacking,the invulnerability experiment investigates the changes of network structure caused by random accidents and targeted management.The dynamics of the cascading failure phenomenon shows that specific management of traffic zone with good connectivity and a limited number of trip chain can achieve good control effect.Then,the travel decision dynamics model is constructed and the travel decision evolutionary mechanism is analyzed.On the basis of the research on the invulnerability of the traffic zones and the travel chains in the structural network,the dynamic mechanism of the travel decision-making stage is discussed and the evolution of the group travel demand is explored from the perspective of whether to choose the travel.The construction of decision model mainly refers to the idea of "tragedy of public land",which highlights the conflict between individual interests and collective interests.By Monte Carlo simulation experiment,the self-organizing intelligent travel group interaction results show that rational behavior helps to inhibit the growth of the travel demand,and the influence of different interaction behavior on travel decision-making process is different.Additionally,rigid demand of travel activity is the cause of high trips during peak hours.Blindly increasing economic punishment measures to control the amount of travel demand is not scientific.Finally,the dynamics model of travel mode choice is constructed and the evolutionary mechanism of travel mode selection is analyzed.According to the research results of travel decision-making behavior,the research object of the travel mode choice stage is determined to be the rigid demander.Based on the qualitative and quantitative characteristics of travel mode choice behavior,this paper discusses the applicability of the demand preference factor model.The evolutionary learning interaction model on the structural network is constructed.According to the results of evolutionary process,the sharing amounts of cars and public transportation can be transferred according to the change of management conditions.Moreover,the development of bicycle superhighways is a beneficial measure,which can inhibit the occurrence of excessive car travel.Based on this,according to the influence among car,public transportation and bicycle superhighways,the reasonable distribution ratio of three travel modes is given.