Simulating Population Behavior: Transportation Mode, Green Technology, and Climate Change
This paper presents a decision tool intended to help achieve the goal of reduction in Green House Gas (GHG) emissions in the greater Philadelphia region by the year 2050. The goal is to explore and build a pre-prototype to evaluate the value of the role for agents, alternative data sources (Census, energy reports, surveys, etc.), GIS modeling, and various social science theories of human behavior. Section 2 explains our initial research on an Agent Based Model (ABM) built upon the Theory of Planned Behavior (TPB) and the Discrete Decision Choice model (DDC) to model consumer technology adoption. The users can utilize the proposed ABM to investigate the role of attitude, social networks, and economics upon consumer choice of vehicle and transportation mode. Finally, we conclude with results on agent decisions for which transit mode to use and whether to adopt greener technologies.
KeywordsAgent Based Models (ABM) Decision-making process Climate change Energy use in transportation Technology adoption
We thank Kleinman Center for Energy Policy, the Mellon Foundation: Humanities, Urbanism, and Design Initiative, and the Delaware Valley Regional Planning Commission for supporting us in this research. Any opinions or errors are those of the authors alone.
- 1.Khansari, N., et al.: An agent-based decision tool to explore urban climate & smart city possibilities. In: 11th Annual IEEE International Systems Conference (SysCon) 2017 (2017)Google Scholar
- 11.Circella, G., Handy, S., Boarnet, M.: Impacts of Gas Price on Passenger Vehicle Use and Greenhouse Gas Emissions, 30 September 2014. http://arb.ca.gov/cc/sb375/policies/policies.htm
- 14.Dunlap, R.E.: At 40, environmental movement endures, with less consensus. Gallup Poll. (2010)Google Scholar