Evolutionary dynamics of traveling behavior in social networks

In this paper, the topology of complex network is used to characterize the interactions among travelers. Based on the assumption of travelers' limited rationality and the wisdom of crowds, an evolutionary game model of travelers was established. Combining these research findings, we study commuters' travel behavior rules during peak traffic periods and make some recommendations that have the potential to relieve traffic congestion. In the first section, we analyze the effect of heterogeneity on travel choice behavior by Monte Carlo simulations, which explains why the total amount of traffic during peak hours is hard to decrease. The experimental results indicate that increasing fees would not reduce traffic flow during peak hours. Moreover, controlling price for the management of travel demand needs to be coordinated with the management of traffic system under the condition of limited road resources. On this foundation, the second section proposes an environmental travel mode for the transfer between cycle highways and rail transit. We verify the effectiveness of this travel mode in alleviating traffic congestion. Furthermore, considering the interactions between different travel modes in transportation system, we suggest some management recommendations with reference to the characteristics of different travel modes. (C) 2019 Elsevier B.V. All rights reserved.yy