From Trend Spotting to Trend Setting: Modeling the Impact of Major Technological and Infrastructural Changes on Travel Demand

Major technological and infrastructural changes are expected to occur over the next decades such as the introduction of autonomous vehicles, advances in
information and communication technology, California High Speed Rail, carsharing and ridesharing, etc. However, this evolution has no defined
path and we should be cautious with how the future is going to play out. We want the future to consist of sustainable and efficient systems. One critical
component in this strategy comprises developing quantitative behavioral analysis tools that focus on modeling and influencing trends of travel behavior to
guide transformative mobility and set it on the right track. Moreover, the potential roles of the government and policy are key in shaping and influencing
the future. This could be achieved by developing quantitative methods that offer insights to planners and policy-makers on what can be done to influence
possible outcomes. In order to tackle and address the general research questions we are interested in, we have addressed three specific components
regarding developing the methodological framework:
1- Projecting membership and market shares of upcoming modes of transport. Developing such a framework will be based on integrating models of
technology adoption and discrete choice analysis (Paper #1).
2- Understanding and predicting structural long-range trends of travel behavior. Developing such a dynamic framework of disaggregate decision-
making will require integrating hidden markov models (HMM) with current travel demand models (Paper #2).
3- While the first two components focus on developing quantitative behavioral analysis tools to guide transformative mobility to ensure a
sustainable and efficient system, we also investigate the adoption and diffusion processes in light of economic theory and its pertinent
literature.