Project 1: Attitude Diffusion

In this project, we presents a model of social network-based attitude diffusion system in the context of activity and travel choice behavior. The primary contributions of this research are

(1) modeling attitude diffusion according to social and learning mechanisms; and
(2) the evolution of these attitudes over time in a lattice neighborhood social network

The agent-based model in this study is implemented in an open source modeling tool NetLogo

Project 2: Route-Choice

Route choice is a daily question that drivers face under variable traffic conditions. Although a variety of studies have focused on route choice behavior, actual route choice behavior on real world networks and the mechanisms that govern it have eluded complete characterization. This study uses an agent-based modeling approach to investigate the effects of social influence on drivers’ route choice. The drivers communicate with each other in the same social network. This information is combined with their previous experiences. The first aim of this study is to investigate the impact of social network connectivity and information exchange on route choice. The second is to characterize when all drivers in the social network are satisfied about their route choices. The simulation results show that a boundedly-rational equilibrium is achieved when all drivers in the given social network are satisfied with their current route choices.